# A Comprehensive Study of the Young Cluster IRAS 05100+3723: Properties,
Surrounding Interstellar Matter, and Associated Star Formation

R. K. Yadav National Astronomical Research Institute of Thailand (NARIT),
Sirindhorn AstroPark, 260 Moo 4, T. Donkaew, A. Maerim, Chiangmai 50180,
Thailand  M. R. Samal Physical Research Laboratory, Navrangpura, Ahmedabad,
Gujarat 380009, India  E. Semenko National Astronomical Research Institute of
Thailand (NARIT), Sirindhorn AstroPark, 260 Moo 4, T. Donkaew, A. Maerim,
Chiangmai 50180, Thailand  A. Zavagno Aix-Marseille Universite, CNRS, CNES,
LAM, Marseille, France  Institut Universitaire de France, Paris, France  S.
Vaddi National Centre for Radio Astrophysics (TIFR), Post Bag 3, Ganeshkhind,
Pune 411007, India  P. Prajapati Physical Research Laboratory, Navrangpura,
Ahmedabad, Gujarat 380009, India  D.K. Ojha Department of Astronomy and
Astrophysics, Tata Institute of Fundamental Research, Homi Bhabha Road, Mumbai
400005, India  A. K. Pandey  deceased  Aryabhatta Research Institute of
Observational Sciences (ARIES), Nainital 263129, India  M. Ridsdill-Smith
National Astronomical Research Institute of Thailand (NARIT), Sirindhorn
AstroPark, 260 Moo 4, T. Donkaew, A. Maerim, Chiangmai 50180, Thailand  J.
Jose  Indian Institute of Science Education and Research (IISER) Tirupati,
Rami Reddy Nagar, Karakambadi Road, Mangalam (P.O.), Tirupati 517 507, India
S. Patra  Indian Institute of Science Education and Research (IISER) Tirupati,
Rami Reddy Nagar, Karakambadi Road, Mangalam (P.O.), Tirupati 517 507, India
S. Dutta Institute of Astronomy and Astrophysics, Academia Sinica, Taipei
10617, Taiwan  P. Irawati  National Astronomical Research Institute of
Thailand (NARIT), Sirindhorn AstroPark, 260 Moo 4, T. Donkaew, A. Maerim,
Chiangmai 50180, Thailand  S. Sharma Aryabhatta Research Institute of
Observational Sciences (ARIES), Nainital 263129, India  D. K. Sahu  Indian
Institute of Astrophysics, II Block, Koramangala, Bengaluru 560 034,
Karnataka, India  N. Panwar Aryabhatta Research Institute of Observational
Sciences (ARIES), Nainital 263129, India

(Revised X, 2021; Accepted Y, 2021)

###### Abstract

We present a comprehensive multiwavelength investigation of a likely massive
young cluster ‘IRAS 05100+3723’ and its environment with the aim to understand
its formation history and feedback effects. We find that IRAS 05100+3723 is a
distant ($\sim$3.2 kpc), moderate mass ($\sim$500 M☉), young ($\sim$3 Myr)
cluster with its most massive star being an O8.5V-type. From spectral
modeling, we estimate the effective temperature and log $g$ of the star as
$\sim$33,000 K and $\sim$3.8, respectively. Our radio continuum observations
reveal that the star has ionized its environment forming an H ii region of
size $\sim$2.7 pc, temperature $\sim$5,700 K, and electron density $\sim$165
cm-3. However, our large-scale dust maps reveal that it has heated the dust up
to several parsecs ($\sim$10 pc) in the range 17$-$28 K and the morphology of
warm dust emission resembles a bipolar H ii region. From dust and 13CO gas
analyses, we find evidences that the formation of the H ii region has occurred
at the very end of a long filamentary cloud around 3 Myr ago, likely due to
edge collapse of the filament. We show that the H ii region is currently
compressing a clump of mass $\sim$2700 M☉ at its western outskirts, at the
junction of the H ii region and filament. We observe several 70 $\mu$m point
sources of intermediate-mass and class 0 nature within the clump. We attribute
these sources as the second generation stars of the complex. We propose that
the star formation in the clump is either induced or being facilitated by the
compression of the expanding H ii region onto the inflowing filamentary
material.

Stars: formation, pre-main-sequence, protostars, clusters $-$ ISM: molecular
clouds, clumps $-$ H ii regions $-$ dust, extinction

††journal: ApJ††facilities: FCRAO, $Gaia$, GMRT, $Herschel$, INT, PANSTARRS1,
$Spitzer$, TNT, UKIRT, VLA.††software: A

##  1 Introduction

Figure 1: The left panel displays the WISE 12 $\mu$m image dust distribution
around the cluster having an area of 30$\times$30 arcmin2, while the right
panel displays the UKDISS $H$-band image of the central 5$\times$5 arcmin2
area.

It is believed that most, if not all, stars form in embedded clusters (Lada &
Lada, 2003). In general, parsec-scale young clusters (age $>$ 2 Myr) have
smooth, centrally condensed and nearly spherical structure (Ascenso et al.,
2007; Harayama et al., 2008), while molecular clouds, in general, have
irregular and much extended (up to tens of parsecs) structure (André et al.,
2008; Molinari et al., 2010). In this context, a key question is “How
centrally condensed clusters form from such molecular clouds?” Although, there
are various proposed mechanisms of cluster formation such as the monolithic
collapse of molecular clouds, hierarchical collapse and merger of gas and
star(s), and global non-isotropic collapse (Longmore et al., 2014; Banerjee &
Kroupa, 2015; Motte et al., 2018; Vázquez-Semadeni et al., 2019), yet it is
unclear that which process plays a dominant role under which circumstances.
Moreover, it is not known if other dynamical processes such as two-body
relaxation and mass-segregation are also responsible to shape the structure of
the newly born clusters (Banerjee & Kroupa, 2017; Sills et al., 2018). These
questions can be addressed by studying young clusters while they are still
associated with gas and dust. Another key question related to cluster
formation, in particular associated with the formation of massive to
intermediate-mass clusters, is whether such clusters play a constructive or
destructive role in the future star formation processes of the host cloud.
Because massive members of such clusters, on one hand, can switch off the star
formation by blowing off the gas and dust from their immediate vicinity, while
on the other hand, they can compress the cold parental gas to promote the star
formation (Elmegreen & Lada, 1977; Deharveng et al., 2010) in the cloud. And
the latter can prolong the star formation activity of a molecular cloud up to
several million years (e.g. Preibisch & Mamajek, 2008). In the past, studying
the early evolution of young clusters had been an observational challenge as
they are buried inside molecular clouds. Recent sensitive surveys over the
last decade, however, have provided a wealth of data in optical to mm domain
(e.g. Jackson et al., 2006; Lawrence et al., 2007; Minniti et al., 2010;
Molinari et al., 2010; Chambers et al., 2016; Gaia Collaboration et al.,
2016). These surveys allow us to better understand the properties of the young
clusters, and characterize the physical conditions of the surrounding
interstellar medium (ISM). For example, by using parallax and proper motion
(PM) measurements obtained from the Gaia (Gaia Collaboration et al., 2016,
2018) survey data, distance to the star clusters can precisely be estimated
(Bailer-Jones et al., 2018) and membership of the bright stars can be well
constrained. Similarly, using deep infrared data sets from surveys such as
UKIDSS (UKIRT Infrared Deep Sky Survey) Galactic Plane Survey (UKIDSS-GPS;
Lucas et al., 2008), Spitzer Galactic Legacy Infrared Mid-Plane Survey
Extraordinaire (GLIMPSE; Whitney & GLIMPSE360 Team, 2009) survey and Wide-
field Infrared Survey Explorer (WISE; Wright et al., 2010) pre-main-sequence
(PMS) members of the young clusters can be identified (e.g. Gutermuth et al.,
2009; Das et al., 2021). Moreover, for moderately extincted nearby clusters,
age determination is possible by constructing color-magnitude diagrams (CMD)
using data from optical surveys such as the $Gaia$ (Gaia Collaboration et al.,
2018), the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS1;
Chambers et al., 2016) and Sloan Digital Sky Survey (SDSS; Alam et al., 2015).
In addition to that, using wide area maps provided by surveys such as Herschel
infrared Galactic Plane Survey (Hi-GAL Pilbratt et al., 2010; Molinari et al.,
2010) and FCRAO (Five College Radio Astronomical Observatory; Jackson et al.,
2006), connections between large-scale environment and the cluster forming
clumps can be made.

In the present work, we characterize the young cluster IRAS 05100+3723 (Bica
et al., 2003) associated with the H ii region Sharpless 228 (hereafter S228,
Sharpless, 1959), also known as LBN 784, and RAFGL 5137
($\alpha_{2000}$=78.∘356250, $\delta_{2000}$=+37.∘450278). The H ii region is
believed to be powered by a massive star ALS 19710 of spectral type between
O8V to B0V, whose reddening ($E(B-V)$), lies in the range 1.2$-$1.3 mag (Chini
& Wink, 1984; Hunter & Massey, 1990). We study the physical conditions of dust
and gas around the cluster by taking advantage of the key strengths of the
aforementioned multiwavelength surveys. Figure 1 shows the WISE 12 $\mu$m
image around the cluster over 30$\times$30 arcmin2 area as well as the central
5$\times$5 arcmin2 area in the near-infrared (NIR) $H$-band from the UKIDSS-
GPS (Lucas et al., 2008) wherein the cluster is clearly visible. There are
several shallow optical and infrared studies on the cluster suggesting that
the cluster is located at a distance between 2.2 and 6.8 kpc and its age lies
somewhere between 1 and 25 Myr (Lahulla, 1985; Hunter & Massey, 1990;
Kharchenko et al., 2013; Yu et al., 2018). To date, the most detailed work on
the cluster has been carried out by Borissova et al. (2003) using NIR
observations. Their results suggest that the age of the cluster is $\sim$3 Myr
and its total stellar mass is $\sim$1800 M☉. This makes the cluster one of the
potential young massive clusters in our Galaxy such as Orion Nebula Cluster
(ONC, mass $\sim$2000 M☉ and age $\sim$3 Myr, see Hillenbrand, 1997; Da Rio et
al., 2010), albeit at a farther distance. Borissova et al. (2003) estimated
the cluster radius to be 1.5 arcmin while Yu et al. (2018) reported the
cluster radius to be 2.5 arcmin.

Intermediate-mass to massive young clusters are rare in our Galaxy. For
example, Lada & Lada (2003), in their study of young ($<$ 3 Myr) embedded
clusters within 2 kpc of the solar neighborhood, found that the only cluster
that has stellar mass $>$ 1000 M☉ is the ONC. Thus, a cluster like IRAS
05100+3723 serves as a potential candidate for understanding the formation and
early evolution of intermediate-mass to massive clusters. Despite the fact
that IRAS 05100+3723 is a potentially young massive cluster, its detailed
stellar content, physical properties, and surrounding ISM are scarcely
explored. In this work, we examine the stellar, gaseous, and dust components
of this likely massive cluster and its environment, with the aim to understand
its formation history and feedback effects on the star formation processes of
the host cloud.

We organize this paper as follows. In Section 2 we present the observations,
archival data sets and data reduction procedures. Section 3 discusses the
stellar content and properties of the cluster, and the physical conditions and
kinematics of the large-scale environment. Section 4 discusses the dynamical
status of the cluster, its formation history, and the effect of stellar
feedback on the star formation scenario of the complex, followed by a summary
in Section 5.

##  2 Observations and Data Sets

###  2.1 Optical Spectroscopic Observations

We obtained medium-resolution spectra for three bright stars in the S228
complex using the Medium Resolution Spectrograph (MRES) mounted on the 2.4 m
Thai National Telescope (TNT). The MRES is a fiber-fed echelle spectrograph
designed to work in spectral range of 3900$-$8800Å with a spectral resolution
of R $\sim$16,000$-$19,000. This instrument is equipped with a 2048$\times$512
pixels Andor CCD camera with a pixel size of 13.5 $\mu$m.

The data were acquired on the night of 2019 March 18 with a lunar illumination
of $\sim$80% during partially cloudy weather conditions. The log of the
observations is given in Table 1. In addition to the science spectra, we
obtained standard calibration frames such as Bias, Flat and Th-Ar lamp. The
data reduction was carried out using the echelle standard package of IRAF. The
spectra were extracted using optimal extraction methods. The wavelength
calibration of the spectra was done using Th-Ar lamp source. The wavelength
calibrated, normalized spectra of the three stars are shown in Figure 2. We
discuss the spectral classification of these stars in Section 3.1.1. It should
be noted that only a part of the spectra, i.e. in the range 4400$-$6800 Å, is
being used in this work. The spectra in the range 3900$-$4400 Å are dominated
by noise due to poor sensitivity in this range and spectra beyond 6800 Å are
dominated by multiple telluric lines/bands and hence not used in our analysis.

Table 1: Log of the MRES observations. ID | $\alpha_{2000}$ | $\delta_{2000}$ | Date of | V | Exposure
---|---|---|---|---|---
| (∘) | (∘) | observation | (mag) | time (sec)
1 | 078.356250 | +37.458222 | 2019-03-18 | 12.6 | 2,700
2 | 078.356667 | +37.458167 | 2019-03-18 | 13.2 | 3,000
3 | 078.353333 | +37.453250 | 2019-03-18 | 13.1 | 3,000

###  2.2 Radio Continuum Observations

Radio continuum observations of the S228 region were obtained at 610 and 1280
MHz using the GMRT array (PI: M.R. Samal, ID: 13MRS01) with the aim to trace
the ionized gas content of the cluster. The GMRT array consists of 30 antennae
arranged in an approximate Y-shaped configuration, with each antenna having a
diameter of 45 m. Details about the GMRT can be found in Swarup et al. (1991).

The Very Large Array (VLA) phase and flux calibrators ‘0555+398’ and ‘3C48’,
respectively, were used for these observations. We carried out the data
reduction using the aips software and followed the procedure described in
Mallick et al. (2013). Briefly, we used various aips tasks for flagging the
bad data and calibrating the data with standard phase and flux calibrators.
Thereafter, we run the aips task ‘IMAGR’ to make maps after splitting the
source data from the whole observations. We applied a few iterations of
(phase) self-calibration to remove ionospheric phase distortion effects. The
resultant maps are discussed in Section 3.2.1.

###  2.3 Ancillary Archival Data Sets

For the present work, we have also used the following archival data sets
covering various wavelengths:

i) $Gaia$ Early Data Release 3 ($Gaia$ EDR3 Gaia Collaboration et al., 2020)
from the European Space Agency Gaia mission (Gaia Collaboration et al., 2016).
We used the kinematic information of Gaia data to estimate the distance to the
cluster. The effective angular resolution of the survey is $\sim$0.4 arcsec.

ii) The Spitzer-IRAC warm mission data at 3.6 and 4.5 $\mu$m data (PI: Barbara
Whitney, Program ID: 61070) from the $Spitzer$ Heritage Archive (SHA). We
acquired the corrected basic calibrated data (cbcd), uncertainty (cbunc), and
imask (bimsk) files. In order to create the final mosaic images with a pixel
scale of 1.2 arcsec pixel-1, and to obtain the aperture photometry of the
point sources, we followed the steps mentioned in Yadav et al. (2016) and used
sources with uncertainty $<$ 0.2 mag for our analysis.

iii) The NIR ($J,H,$ and $K$) photometric data, from the UKIDSS-GPS (Lucas et
al., 2008), with uncertainty $<$ 0.2 mag in all three bands. The spatial
resolution of the UKIDSS-GPS data is in the range 0.8$-$1 arcsec.

iv) The INT/WFC Photometric H$\alpha$ Survey of the Northern Galactic Plane
(IPHAS) data release 2 (Barentsen et al., 2014) photometric data with
uncertainty $<$ 0.2 mag in Sloan $r$, $i$ broad-band and H$\alpha$ narrow-band
filters. The spatial resolution of the IPHAS data is in the range 0.8$-$1
arcsec.

v) The Pan-STARRS1 (hereafter; PS1 Chambers et al., 2016) survey photometric
data with uncertainty $<$ 0.2 mag in $i_{\rm{P1}}$ and $z_{\rm{P1}}$ bands
were used to estimate the age of the cluster. The spatial resolution of the
PS1 data is in the range 0.8$-$1 arcsec.

vi) The far-infrared images from the Herschel infrared Galactic Plane Survey
(Hi-GAL) (Molinari et al., 2010) images at 70, 160, 250, 350, and 500 $\mu$m
were used. The spatial resolution of the Hi-Gal observation at 70, 160, 250,
350, and 500 $\mu$m bands is 8.5, 13.5, 18.2, 24.9, and 36.3 arcsec,
respectively.

vii) The radio continuum image at 8700 from the National Radio Astronomy
Observatory (NRAO) data archive (Project ID: AR390). The beam size of the
image is $\sim$10 arcsec$\times$ 8 arcsec while its rms noise is $\sim$0.1
$\mu$Jy beam-1.

viii) The radio continuum image at 150 MHz from the TIFR GMRT Sky Survey
(TGSS) (Intema et al., 2017). The typical resolution of the TGSS images is
$\sim$25 arcsec$\times$25 arcsec with a median noise of $\sim$3.5 mJy beam-1.

####  2.3.1 Completeness of Photometric Data

In this work, we used UKDISS, Spitzer-IRAC and IPHAS data sets to access the
young stellar contents of the cluster. We obtained the completeness limits of
these bands using the histogram turnover method. Although this method is not a
formal tool to measure the completeness, it serves as a proxy to give the
typical value of completeness limit across the field (e.g. Samal et al., 2015;
Damian et al., 2021). In this approach, the magnitude at which the histogram
deviates from the linear distribution is, in general, considered as 90%
complete. Figure 3 shows histograms of sources detected in various bands over
a radius $\sim$2.5′(see Section 1). The above approach suggest, in general,
our photometry is $\sim$90% complete down to $J$ = 17.8 mag, $H$ = 16.8 mag,
$K$ = 16.2 mag and [4.5] = 15.5 mag, these are marked by vertical lines in
Figure 3. Similarly, we also estimated the completeness limits of IPHAS $r$,
H$\alpha$ , and $i$; and PS1 $i_{\rm{P1}}$ and $z_{\rm{P1}}$ bands as 20.3
mag, 19.8 mag, and 19.0 mag; and 20.4, and 19.7 mag, respectively.

Figure 2: Continuum normalized and scaled spectra of three bright stars #1,
#2, and #3 observed with MRES mounted on TNT. Important stellar lines are
marked. Figure 3: Histograms of the sources detected in $J,H,K$, and [4.5]
$\mu$m photometric bands. The vertical red lines indicate the 90% completeness
limit. See the text for details.

##  3 Analysis and Results

###  3.1 Stellar Content and Properties of the Cluster

In this section, we access massive and low-mass stellar contents of the
cluster and derive cluster properties using various photometric catalogs.

####  3.1.1 Spectral Classification and Modeling of the Bright Sources

Figure 4: Pan-STARRS $r$-band image of the cluster along with the sources for
which spectroscopic observations have been conducted. The ID and the
coordinates of the sources are given in Table 1.

The cluster IRAS 05100+3723 is associated to an H ii region, implying that its
massive members must be responsible for the ionization of the region. To
identify the ionizing source(s) of the H ii region, we selected three bright
sources located within the region of strong H$\alpha$ emission. Following
Comerón & Pasquali (2005), we use the infrared reddening-free pseudo color
index, Q = ($J-H$) $-$ 1.70$\times$($H-K$) and select sources with Q $<$ 0.1
as probable OB stars of the region. These sources are marked in Figure 4 as
#1, #2, and #3. However, selected sources may be contaminated by objects such
as AGB stars, carbon stars, and A-type giants (Comerón & Pasquali, 2005). We
thus performed optical spectroscopic analyses of these three bright sources.

As mentioned in Section 2.1, observations were carried out under the cloudy
weather conditions during the waxing Moon with 80% illumination. This caused
the stellar spectra to be heavily contaminated with the solar lines. The
contamination becomes more obvious upon close examination of the spectra
(Figures 2, and 5). The variable contamination of stellar spectra restricts
our capabilities to find the accurate physical parameters of the stars, but
the spectra still contain enough markers of the effective temperature.

The abundance of neutral and/or ionized helium lines in absorption is
indicative of O or early B type main sequence stars. These lines may be in
emission in case of giants/super giants. The strength of He ii 4686 gets
weaker for late O-type stars, and this line is last seen in B0.5 stars
(Walborn & Fitzpatrick, 1990). We could find such lines only in the spectrum
of the star #1. To further constrain this, we compare our data with synthetic
spectra computed for different combinations of effective temperature, surface
gravity, and projected rotational velocity. Theoretical spectra were
synthesized with Synplot, an IDL-based wrapper of the Synspec package for
spectral synthesis (Hubeny & Lanz, 2011). We use “OSTAR2002” grid of pre-
computed models of Lanz & Hubeny (2003).

Figure 5: Part of the MRES spectrum (red) for the source #1 fitted with a
synthetic profile (black). The synthetic spectrum was computed using the
parameters specified in the text.

In the observed spectrum, we identified multiple neutral and ionized helium,
carbon, and oxygen lines (Figure 5). Among them, two helium lines He I
$\lambda 4471$ and He II $\lambda 4541$ are good indicators of effective
temperature. The intensity ratio of these lines equals to 1 for the spectral
class O7 (Walborn & Fitzpatrick, 1990) and it varies between $>$ 1 and $<1$
for the spectral range O5$-$O9. This intensity ratio for star #1 is estimated
to be $<1$. By fitting synthetic spectrum, we derive the effective temperature
$T_{eff}=33,000\pm 1000$ K and surface gravity $\log g=3.8\pm 0.5$ (Figure 5),
which allowed us to classify this object as an O8.5V$\pm$0.5 star. The
synthetic spectrum was computed for $T_{eff}=33,000\pm 1000$ K, $\log g=3.8\pm
0.5$, and $v\sin i=100\pm 50$ km/s for the whole wavelength range, which
agrees well with the observed lines in other spectral regions and thereby
verifies our estimates.

The spectral types of the two fainter stars are less certain. Their spectra do
not contain any measurable lines of helium, which are typical of OB stars.
Instead, from the comparison with the solar spectrum we identified neutral
iron, chromium and titanium (see Figure 2) lines. Detailed modelling of these
spectra was carried out using the NEMO grids of stellar atmospheres computed
with a modified version of the ATLAS9 code (Heiter et al., 2002). The
modelling results show that the star #2 is hotter than the Sun and has an
effective temperature $7000\pm 1000$ K whereas the star #3 looks comparatively
cooler with a probable effective temperature of 6400 K. The existing data do
not allow us to determine the surface gravity (and thus the evolutionary
status) of these stars with higher accuracy. Our spectral analysis suggests
that stars #2 and #3 are late A to F type stars. Indeed, the Gaia data
confirmed that stars #2 and #3 are the foreground objects, as discussed in
Section 3.1.3.

####  3.1.2 Physical Extent

Figure 6: Upper Panel: Stellar surface density map of S228, made using the
nearest neighbors method. The color bar represents the stellar surface density
in the units of stars per arcmin2. Contours correspond to stellar surface
densities above $3\sigma$ of the mean background density, where $\sigma$ is
the standard deviation of the background density. The green circle represents
the cluster region whose radius was obtained using the radial density profile
fitting method shown in the lower panel. Lower Panel: The observed stellar
surface density (filled circles) of S228 as a function of radius. The
horizontal line represents the mean density level of the field stars. The
continuous curve shows the fitted King’s profile to the observed data, while
the shaded area represents the $1\sigma$ error associated to the fitted
profile. The error bars represent the Poisson uncertainties.

We derived the physical extent of the cluster by generating the stellar
surface density map (SSDM) using UKDISS point sources. In order to generate
the SSDM map, we use the nearest neighbors algorithm as described in Gutermuth
et al. (2005). Succinctly, at each sample position [$i,j$] in a uniform grid,
we measured $r_{N}$($i,j$), the projected radial distance to the $N^{th}$
nearest star. $N$ is allowed to vary to the desired smallest scale structures
of interest. We generated the map using $N$=20, which, after a series of
tests, was found to be a good compromise between the resolution and signal-to-
noise ratio of the map. The resultant map is shown in Figure 6 (upper panel)
along with stellar surface density contours. We then considered the peak (at
$\alpha_{2000}$= 78.∘366083 $\delta_{2000}$= +37.∘444889) of the SSDM map as
the cluster center.

We also constructed a radial density profile (RDP) of the cluster. The RDP is
generated by plotting the annular stellar density against the corresponding
radius (for details, see Panwar et al. (2019)). In order to parametrize the
RDP, the observed RDP is fitted with the empirical King’s profile (King,
1962), which is of the form:

$\rho(r)\propto
b_{0}+\frac{\rho_{0}}{\left(1+\left(\frac{r}{r_{c}}\right)^{2}\right)}$ (1)

where b0, $\rho_{0}$ and $r_{c}$ are the background stellar density, peak
density, and core radius, respectively. The fitted King’s profile, shown in
the lower panel of Figure 6, yields a central density of $\rho_{0}$ = 116
stars arcmin-2, a core radius of $r_{c}$ = 0.8 arcmin and a background density
$b_{0}$ = 13 stars arcmin-2. From Figure 6, we note that the model profile
merges with the background density at 2.5 arcmin and is almost constant beyond
the radius of $\sim$3.0 arcmin. We thus considered the radius of the cluster
to be 2.5 arcmin. The estimated radius is in agreement with the cluster size
of 5.2 arcmin (or radius of 2.6 arcmin) reported in Yu et al. (2018). A circle
of thus estimated radius is also over plotted on the SSDM, which is in good
agreement with the size of the SSDM map.

####  3.1.3 Distance

Figure 7: Proper-motion vector diagram (PVD) for all the sources toward S228
within the cluster region. Sources distributed in the red zone represent the
likely cluster members.

The distance of S228 is quite uncertain, ranging from 2.2 to 6.8 kpc (Lahulla,
1985; Hunter & Massey, 1990; Borissova et al., 2003; Balser et al., 2011;
Kharchenko et al., 2013). With the aim to tighten the distance of the cluster,
we searched for the kinematic members of the cluster using the Gaia EDR3
catalog. Figure 7 shows the proper-motion vector diagram (PVD) of relatively
bright sources ($G$ $<$ 18 mag) within the cluster radius. As can be seen,
there are two likely distributions in the PVD, i) a compact group consisting
of sources of similar motion (marked with red zone), thus are considered as
cluster members, and ii) a loose group of sources showing scattered motion,
thus are considered as field sources. A clear separation between the cluster
and field stars motion enables us to select member stars of S228 relatively
reliably. Among the compact group sources, we reject a few outliers, by
keeping only those sources whose parallax ($\varpi$) values are within one
standard deviation of the median parallax of the group and have good relative
parallax uncertainties ($\varpi$/$\sigma_{\varpi}$ $>$ 5). The latter
condition is primarily motivated by the fact that, if fractional parallax
errors are less than about 20%, then the posterior probability distribution of
parallax is nearly symmetric (Bailer-Jones, 2015), hence, distance can simply
be computed by inverting the parallax. With these constraints, 7 sources are
found to have common proper motions (PM) and parallaxes. We find that among
these sources, the ionizing source (i.e. star #1) is one of the members, while
the other bright spectroscopic sources (i.e. star #2 and #3) are not members,
confirming our spectroscopic membership. The PM in Right Ascension
($\mu_{\alpha}$), PM in Declination ($\mu_{\delta}$) and parallax ($\varpi$)
values of these sources lie in the range $-0.10$ to 0.37 mas yr-1, $-1.45$ to
$-1.30$ mas yr-1 and 0.28 to 0.39 mas, respectively, with median -0.01 $\pm$
0.15 mas yr-1, $-$1.40 $\pm$ 0.06 mas yr-1, and 0.31 $\pm$ 0.04 mas. From the
median parallax value, we estimated the distance of the cluster to be 3.2
$\pm$ 0.4 kpc, which is in agreement with the kinematic distance of 3.5 kpc,
very recently derived by Mège et al. (2021) using velocity analysis of the
molecular gas associated to the region.

####  3.1.4 Pre-Main-Sequence Members

In the absence of spectroscopic or kinematic information of low-mass sources,
optical and infrared color-color (CC) diagrams are often used as diagnostic
tools to identify the likely PMS members in a star-forming region (e.g. Lada &
Adams, 1992; Barentsen et al., 2011). In this work, we used IPHAS, UKIDSS-GPS,
and Spitzer-IRAC point source catalogs above the completeness levels and
employed CC diagrams to search for the PMS stars with either excess NIR
emission due to the presence of circumstellar disc or excess H$\alpha$
emission due to accretion onto the stellar photosphere. The details about the
CC diagrams and the identified sources are given below.

#####  H$\alpha$ Excess Emission Sources

The ($r-$H$\alpha$ ) color measures the strength of the H$\alpha$ line
relative to the $r-$band photospheric continuum. Since most main-sequence
stars do not show H$\alpha$ emission, their ($r-$H$\alpha$ ) color, which is
linked to spectral type, provides a template, against those whose
($r-$H$\alpha$ ) color excess caused by H$\alpha$ emission. Moreover, in the
($r-$H$\alpha$ , $r-i$) CC space, interstellar reddening has minimal effect on
($r-$H$\alpha$ ) color as the reddening moves only the unreddened MS track
almost with a right angle to the ($r-$H$\alpha$ ) color. Thus, in star-forming
complexes, the ($r-$H$\alpha$ , $r-i$) diagram is often used to discern
H$\alpha$ emission line stars (Barentsen et al., 2011; Dutta et al., 2015).
The ($r-$H$\alpha$ , $r-i$) CC diagram for the stars in the direction of S228
is shown in Figure 8. The running average ($r-$H$\alpha$ ) color of the stars
as a function of their ($r-i$) color is shown with a solid line, while its
10$\sigma$ uncertainty is shown with a shaded area. Figure 8 shows the
($r-$H$\alpha$ , $r-i$) color of the main-sequence (MS) track taken from Drew
et al. (2005) for $A_{\it V}$ $\sim$3.1 mag. Using this diagram, those sources
with ($r-$H$\alpha$ ) color excess greater than 10$\sigma$ of the average
color of the stars are considered as probable emission line sources, and are
marked with red circles. With this approach, we identified 21 likely H$\alpha$
excess sources.

Figure 8: The IPHAS CC ($r-$ H$\alpha$ , $r-i$) diagram of the point sources
in the direction of the cluster. The median ($r-$H$\alpha$ ) color of the
field sources and 10$\sigma$ limits around the median color line (blue) is
shown with a shaded area. The red curve represents the synthetic MS track
taken from Drew et al. (2005) corresponding to E(B-V) = 1.0 mag (or $A_{\it
V}$ $\sim$3.1 mag). The filled red circles are the probable H$\alpha$ excess
candidates within the cluster area.

##### Near-Infrared Excess Emission Sources

Figure 9: Left: The ($J-H$, $H-K$) CC diagram for the cluster region and the
control field region. The green curves are the intrinsic dwarf locus from
Bessell & Brett (1988). Right: The ($H-K$, $K-$ [4.5]) CC diagram for the
cluster region and the control field region. The green curves are the
intrinsic dwarf locus of late M-type dwarfs (Patten et al., 2006). In all the
plots, the blue lines represent the reddening vectors drawn from the location
of M6 dwarf, while the red circles represent likely NIR$-$excess sources.

The NIR ($J-H$, $H-K$) diagram is a useful tool to identify PMS sources
exhibiting NIR$-$excess emission. However, other dusty objects along the line
of sight may also appear as NIR$-$excess sources in the CC diagram. One
possible way to separate out PMS sources is to compare the CC diagram of the
cluster with that of a nearby control field of the same area and photometric
depth. The left panel of Figure 9 shows NIR CC diagrams of the cluster as well
as a control field (centered at $\alpha_{2000}$= 78.∘382386, $\delta_{2000}$=
37.∘17977) located $\sim$5 arcmin away from the cluster field. In the NIR CC
diagram, sources distributed left to the reddening vector (blue line) can be
field stars or reddened MS stars or weak-line T$-$Tauri stars, while sources
located right to the reddening vector are considered as PMS sources with
NIR$-$excess (Lada & Adams, 1992). As can be seen in Figure 9, compared to the
cluster region, the NIR$-$excess zone of the control field is devoid of
sources, implying the presence of true NIR$-$excess sources in the cluster
region. However, in order to separate spurious sources, if any, from genuine
excess sources we selected sources based on the following criteria: i) sources
with ($J-H$) color greater than 0.7 mag because the maximum ($J-H$) color of
the control field population is around 0.7 mag, and ii) sources that fall to
the right of the reddening vector with ($H-K$) color excess larger than the
uncertainties in their respective ($H-K$) colors. With this approach, we
identified 14 NIR-excess candidate sources within the cluster region. These
sources are identified as red circles in Figure 9.

It is well known that circumstellar emission from young stars dominates at
longer wavelengths, where the spectral energy distribution (SED) significantly
deviates from the pure photospheric emission. We thus use Spitzer-IRAC
observations in combination with $JHK$ data to identify additional
NIR$-$excess sources. For this purpose, we use the ($H-K$, $K-$[4.5]) CC
diagram, shown in the right panel of Figure 9. It should be noted that we
preferred 4.5 $\mu$m data over 3.6 $\mu$m as it is less affected by Polycyclic
aromatic hydrocarbon (PAH) emission, which is often present in the H ii region
environments (Smith et al., 2010). Similar to ($J-H$, $H-K$) analysis, we
compared the distribution of cluster sources with control field sources, then
selected NIR$-$excess sources whose excess emission is more by the error
associated to the $K-[4.5]$ color of the sources and ($H-K$) color greater
than 0.4 mag. With this approach, we identified 25 additional candidate stars
with NIR excess. This makes 39 NIR excess sources in total.

In summary, with the above approaches, we identified 21 likely H$\alpha$
emission line sources and 39 NIR excess sources. Among 21 H$\alpha$ sources, 6
sources are found to have NIR excess counterparts. In total, within the
cluster region, we identified 54 PMS sources. Out of the 54 PMS sources, 52
sources have optical counterparts in the Pan-STARRS1 bands, and are used to
derive the age of the cluster.

####  3.1.5 Extinction

We derived visual extinction of the cluster using its likely OB members.
Briefly, we select OB stars from the Gaia member sources (e.g, see Samal et
al., 2010) identified in Section 3.1.3 by considering only those sources whose
Q value is $<$ 0.1 showing no NIR excess. This resulted in five sources out of
the seven Gaia members. We then derived the ($H-K$) color excess, $E(H-K)$, of
the members from the observed and intrinsic ($H-K$) colors. Since the most
massive star of the cluster is an O8.5V star, we thus adopted an intrinsic
($H-K$) color of $\sim$0.03 mag for our analysis, which is the mean intrinsic
color of O8 to B9 MS stars as tabulated in Pecaut & Mamajek (2013). We then
estimated the visual extinction of the sources using the relation, $A_{V}$ =
15.9 $\times$ $E(H-K)$, adopting the extinction laws of Rieke & Lebofsky
(1985). This yields a mean visual extinction $A_{\it V}$ = 3.3 $\pm$ 0.6 mag,
which is in agreement with the extinction measurements between 3.0 mag
(Lahulla, 1985) and 3.9 mag (Hunter & Massey, 1990) derived for S228.

####  3.1.6 Age

Figure 10:  The optical ($i_{\rm{P1}}$, [$i_{\rm{P1}}$\- $z_{\rm{P1}}$]) CMD
of the control field (left panel) and cluster region (right panel). In the
cluster CMD, the NIR$-$excess sources identified based on $JHK$ and $HK[4.5]$
bands are shown by red and green circles, while the H$\alpha$ excess sources
are shown by blue circles, and the PM based massive members are shown by cyan
circles. In cluster CMD the PMS isochrones of ages 0.1, 1, 3, 5, 7 and 10 Myr
from Dotter (2016) are shown from left to right, while the blue solid curves
in both the CMDs represent the ZAMS isochrone, to guide the distribution of
filed stars in both the plots. All the PMS isochrones are corrected for a
distance of 3.2 kpc and an average reddening of $A_{\it V}$ = 3.3 mag. In both
the plots, the reddening vectors corresponding $A_{\it V}$ =0.5 mag are shown
by slanted arrows.

Figure 11: The (gravity ($g$), temperature ($T_{eff}$)) diagrams for the
massive star. In the upper panel, the thin solid curves are the MESA
isochrones for ages 2, 4, 6, and 10 Myr, while in the lower panel the dashed
lines are the evolutionary tracks for 20, 25, 30 and 35 M☉.

The ages of young clusters are typically derived by fitting theoretical PMS
isochrones to the low-mass contracting population. To derive the age of IRAS
05100+3723, we use optical ($i_{\rm{P1}}$, [$i_{\rm{P1}}$$-$$z_{\rm{P1}}$])
CMD of the PMS sources identified in Section 3.1.4 as the cluster members. We
chose $i_{\rm{P1}}$ and $z_{\rm{P1}}$ bands to derive the age, as both of
these bands have higher PMS counterparts over other bands of the PS1 survey.
Moreover, benefits of using optical bands are that i) it minimizes the effect
of the excess emission compared to NIR bands, and ii) it minimizes the effect
of differential reddening as the reddening vectors are nearly parallel to the
isochrones. Figure 10 shows the ($i_{\rm{P1}}$,
[$i_{\rm{P1}}$$-$$z_{\rm{P1}}$]) CMDs of the cluster (right) as well as the
nearby control field (left). In the cluster CMD, all the sources within the
cluster area and the likely PMS sources are shown with grey dots and filled
circles, respectively. We find that the average $A_{\it V}$ of the control
field population is likely around 2.3 mag, which is estimated by matching a
reddened theoretical "zero-age main sequence" (ZAMS) with the observed
population. To guide our analysis, we have also plotted ZAMS at $A_{\it V}$ =
2.3 mag on the cluster CMD. A careful comparison of the distribution of the
PMS sources and the control field sources on the CMD reveals that the majority
of the PMS sources are redder compared to the ZAMS isochrone at $A_{\it V}$ =
2.3 mag. Comparison of both the diagrams reveals that the field population is
quite significant in the direction of the cluster.

Next, we over-plotted MESA (Modules for Experiments in Stellar Astrophysics)
isochrones (Dotter, 2016) on the CMD after correcting them for the adopted
distance of 3.2 kpc and extinction of $A_{\it V}$ = 3.3 mag. The adopted
extinction value is also found to match well with the bright PM based cluster
members, implying that for the cluster, the average $A_{\it V}$ = 3.3 mag is a
reasonable assumption. We note that compared to the field population, the
extra extinction of $A_{\it V}$ = 1 mag observed in the direction of the
cluster could be intrinsic to the cluster. In fact, we find that the cluster
is still associated with gas and dust as seen in Figure 22 supporting the
above hypothesis. As can be seen from Figure 10 the location of most of the
PMS sources are in the age range 0.1$-$10 Myr, implying that the cluster is
young. We note that a small fraction of H$\alpha$ emitting sources are found
to be close to the field distribution. Such sources could be contaminants such
as carbon stars, white dwarfs, and/or interacting binaries (for details, see
Barentsen et al., 2011). In this analysis, we consider all the PMS sources
younger than 10 Myr as most likely cluster members, because the level of
accretion activity for PMS sources older than 10 Myr is expected to be very
low (Williams & Cieza, 2011). Then we derive the age of the individual PMS
sources by comparing their location with isochrones having age between 1 and
10 Myr with an interval of 0.1 Myr. We assign PMS sources an age equal to the
age of the closest isochrone. In this process, some sources located to the
right of the 0.1 Myr isochrone are simply considered to have an age of 0.1
Myr. Doing so, we estimate the mean age of the PMS sources, thus of the
cluster, to be $\sim$2.1 $\pm$ 1.3 Myr. Although the smaller sample of PMS
sources and variable extinction limit us to derive a very precise age of the
cluster, yet it agrees well with the age estimates of Borissova et al. (2003).

To ascertain our result, we further use the properties of the massive star
derived in Section 3.1.1. To do so, we compared the derived $T_{eff}$ and log
$g$ of the star with the MESA isochrones and stellar evolutionary tracks as
shown in Figure 11. As can be seen, because of a large error in log $g$ value,
the location of the star in Figure 11 spans over a wide range of mass and age.
Although accurate stellar parameters are needed to constrain the age of the
star more precisely, nonetheless, we use the Bayesian approach implemented in
the isochrones package (Morton, 2015) to derive the most probable age and mass
of the star. The isochrones package uses the nested sampling scheme MULTINEST
(Feroz et al., 2009) to capture the true multi-modal nature of the posteriors.
Figure 12 shows the obtained posterior probability confidence contours of mass
and age with the Bayesian approach. The peak of the likelihood distribution is
considered as the most probable value, and the estimated uncertainty is
determined by considering 15 and 85 percentile values of the likelihood
distribution. With this approach, we find the most probable age of the star to
be $\sim$4 Myr, while the most probable mass to be $\sim$20 M☉. If one takes
the average uncertainty associated to the most probable value, then the age,
4.0 $\pm$ 2.7 Myr, is in reasonable agreement with the age, 2.1 $\pm$ 1.3 Myr,
derived using CMD of the low-mass stars.

With these two approaches, the average age turns out to be 3.0 $\pm$ 1.5 Myr,
which we considered as the age of the cluster for further analyses. Since the
cluster is associated with an H ii region that is still bright in optical and
radio bands, thus one would expect the cluster to be young. Our analysis
confirms this hypothesis.

Figure 12: The lower-left plot shows the posterior probability distributions
of mass and age of the massive star obtained from the isochrone fitting. The
upper-left and lower-right plots are the probability distribution histograms
for the mass and age, respectively. The middle line in the histogram plots is
the median value of the distribution, while the left and right lines represent
the 16% and 84% percentile values, respectively.

####  3.1.7 Mass Function and Total Stellar Mass

Figure 13:  The ($J$, $J-H$) CMDs of the cluster (red dots) and the control
field (blue dots). In the left panel, control field sources are plotted
without any reddening correction, while in the right panel an extra reddening
corresponding to $A_{\it V}$ = 1.0 mag have been applied to control field
sources.

Figure 14: Left Panel: The green and blue histograms represent the $J$-band
luminosity functions of the cluster and control fields, respectively, while
the luminosity function after correcting for the field-star contamination is
shown with the red histogram. The control field is reddened by $A_{\it V}$ = 1
mag. In the plot, the vertical dashed line represents the $\sim$90%
completeness limit of the $J$-band, while the error bars represent the Poisson
uncertainties. Right Panel: Present-day mass function of the cluster computed
from the field-star decontaminated $J$-band luminosity function and is shown
by dots. The 90% mass completeness limit of the data in terms of mass is shown
by a vertical dashed line. The fitted power law of the observed mass function
is shown by a blue line and is extended towards the low-mass end using the
functional form of the mass function given by Kroupa (2001).

The stellar initial mass function (IMF) describes the mass distribution of the
stars in a stellar system during birth and is fundamental to several
astrophysical concepts. For a young cluster, IMF is in general derived from
the luminosity function of member stars above the completeness limit. In our
case, adopting the estimated age and extinction of the cluster, we find the
photometric completeness limits of our $J,H,$ and $K$ bands (see Section 2.3)
correspond to mass completeness limits of 0.6 M☉, 0.6 M☉, and 0.7 M☉,
respectively. We then used the $J$-band luminosity function (JLF) to derive
the IMF. The selection of the $J$-band is motivated mainly by the fact that
the effect of circumstellar excess emission in the $J$-band is minimum
compared to the $H$ and $K$ bands (see Section 2.3.1), and moreover its mass
sensitivity is comparable to these bands. Figure 13 (left panel) shows the
($J$, $J-H$) CMD for the cluster as well as the control field. As can be seen
from the figure, the cluster region (red dots) appears to have bi-modal color
distributions, in which a group of redder sources with $J$ $>$ 16.0 mag are
relatively well separated from a group of bluer sources. This implies that the
redder sources are likely the cluster members, while the bluer sources are
likely the field population in the direction of the cluster. One may also
notice that compared to the ($i_{\rm{P1}}$, [$i_{\rm{P1}}$\- $z_{\rm{P1}}$])
CMD shown in Fig. 10, the ($J,J-H$) CMD shows a richer population of young
sources. This could be due to the fact that infrared bands are less affected
by extinction, and also young sources are intrinsically bright at longer wave
bands. In the present case, we have detected 112 extra sources in $J$ and $H$
bands compared to $i_{\rm{P1}}$ and $z_{\rm{P1}}$ bands.

One can also see from the figure that the distribution of the likely field
population of the cluster matches well with the distribution of the control
field sources (blue dots), but appears to be slightly redder. To match the
control population with the field population of the cluster, we reddened the
control population with a reddening corresponding to $A_{\it V}$ = 1 mag
(3.3$-$2.3 mag), as discussed in section 3.1.6. Here, we assume that most of
the field population in the direction of the cluster is in the background of
the cluster. In doing so, we found that the distribution of the field
population of the cluster matches well with the control population in both
color and photometric depth (see Figure 13, right panel).

Figure 14 (left panel) shows the JLF of the cluster, the reddened field
population, and the field subtracted cluster population. As can be seen that
the JLF at the low-luminosity end, beyond $J$ = 18 mag, shows a declining
trend, which we attribute to the incompleteness of the data beyond $J$ = 17.8
mag. We then constructed the present-day mass function (see Figure 14 (right
panel)) from the field star subtracted luminosity function using the mass-
luminosity relation for a 3 Myr MESA isochrone. Although the completeness
limit of our $J$-band data keeps us from drawing any conclusions on the peak
of the IMF and the shape of the IMF towards the lower mass (M $<$ 0.6 M☉) end,
but in general in star clusters, the peak in the stellar distribution lies in
the mass range 0.2 $-$ 0.7 M☉ (e.g. Neichel et al., 2015; Damian et al.,
2021). Future deeper observations of the region would shed more light on the
shape of the IMF towards the lower-mass end. Nonetheless, a simple power law
fit to the data over mass range $\sim$3$-$0.6 M☉ resulted in a slope of
$\alpha$ = $-$2.3 $\pm$ 0.25, which is comparable to the canonical value of
$\alpha$ = $-$2.35 given by Salpeter (1955) or $\alpha$ = $-$2.3 given by
Kroupa (2001) for the mass range 0.5 $-$ 10 M☉. This implies that the IMF of
the cluster at the high-mass end is similar to other Galactic clusters. We
then estimated the total stellar mass of the cluster, assuming that Kroupa’s
broken power-law (shown in Figure 14) holds true down to 0.08 M☉. Since the
most massive star of the cluster is of $\sim$20 M☉, thus, we integrated the
mass function over the mass range 20$-$0.08 M☉ which yields a total stellar
mass of $\sim$510 M☉. It should be noted that using a mass function slope
$\alpha=-2.33$ and integrating over the mass range 20 $-$ 0.1 M☉, Borissova et
al. (2003) have estimated the mass of the cluster to be 1800 M☉. For
comparison, if we use a single power-law slope of -2.3 between 20$-$0.1 M☉, we
find the total cluster mass to be $\sim$900 M☉. Even though our mass
estimation is done over a larger area (i.e. over 2.5′ radius) yet we obtained
stellar mass less by a factor between two and four compared to Borissova et
al. (2003). The exact reason of this discrepancy is not known, however, it is
worth noting that Borissova et al. (2003): i) did not use deep control field
observations for field star subtraction, instead, they used 2MASS data for the
field population assessment, and ii) we have used reddened control population
to match the depth and color of the likely field population in the cluster
region, and iii) they used $K$-band luminosity function for their analysis,
while we use $J$-band luminosity function. These factors could be the possible
reasons for the discrepancy in the total cluster mass estimation.

The empirical relation between the mass of the most massive star
($m_{\mathrm{max}}$) of a cluster and its total mass ($M_{\mathrm{ecl}}$) is
given by Bonnell et al. (2004) as:

$m_{\mathrm{max}}^{\mathrm{Bonnell}}=0.39\times M_{\mathrm{ecl}}^{2/3}.$ (2)

Using the Bonnell et al. (2004) relationship, we estimated that for a cluster
like, IRAS 05100+3723, whose most massive star is a $\sim$20 M☉ star. One
would expect the total cluster mass to be $\sim$400 M☉, consistent with our
cluster stellar mass estimation. Based on our results, it can be inferred that
IRAS 05100+3723 is a moderate mass cluster
($100\mbox{M${}_{\sun}$}<M_{cl}<1000\mbox{M${}_{\sun}$}$) in the
classification scheme of Weidner et al. (2010).

###  3.2 Physical Environment and Large-scale Distribution of Gas and Dust

####  3.2.1 Ionized gas Properties and Distribution

Figure 15: Radio maps of the H ii region S228 at 150, 610, 1280 and 8700 MHz,
showing the distribution of ionized emission at different bands. The grey
scale bar shows the intensity of radio emission in the units of mJy/beam.
Figure 16: Comparison between emission at 8700 MHz (green contours), 150 MHz
(red contours) and optical H$\alpha$ emission (grey scale background image) of
the H ii region. The contours are drawn above the five times of the rms noise
of the respective maps. The 8700 MHz contour levels are at 0.0005, 0.0035,
0.0065, and 0.0095 Jy/beam, whereas the 150 MHz contours are at 0.015, 0.022,
0.029, 0.036 and 0.044 Jy/beam. Figure 17: The SED of the H ii region S228
combining flux at 150, 610, 1280 and 8700 MHz. These measurements represent
the fluxes integrated over a circular area of effective radius 0.7 arcmin
($\sim$0.7 pc). The solid line represents the fitted free-free emission model,
while the shaded area represents the 1$\sigma$ uncertainty associated to the
fit.

As discussed in Section 1, the cluster is associated with the H ii region
S228. Figure 15 shows the maps of the H ii region at 150, 610, 1280 and 8700
MHz. These maps include GMRT observations at 610 MHz (beam size
$\sim$6.6″$\times$ 3.4″, rms noise $\sim$0.2 mJy/beam) and 1280 MHz (beam size
$\sim$10 ″$\times$ 8″, rms noise $\sim$0.4 mJy/beam), along with 8700 MHz map
(beam size $\sim$10.5″$\times$ 7.5″, rms $\sim$0.1 mJy/beam) from the VLA
archive and 150 MHz map (beam size $\sim$25″$\times$ 25″, rms $\sim$3.0
mJy/beam) from the GMRT TGSS survey.

In interferometric observations, low-level diffuse emission is often found to
be missing in high-resolution and/or high-frequency observations. Despite the
fact that the 150 MHz map is of low-resolution, we find that compared to other
bands the ionized emission at 150 MHz, however, is seen only in the central
area (e.g. see Figure 16). This could be due to the lower sensitivity of the
150 MHz observations.

Normally, the free-free emission from a homogeneous classical H ii region
shows a rising SED with flux (S${}_{\nu})\propto\nu^{2}$ at lower frequencies
and almost flat SED with S${}_{\nu}\propto\nu^{-0.1}$ at higher frequencies.
However, the true behavior of Sν with respect to $\nu$ strongly depends on the
evolutionary status of the H ii region and can be well constrained with the
thermal free-free emission modeling. Since the emission from 150 MHz is coming
only from the inner region of an effective radius of $\sim$0.7′, we thus
integrated fluxes at 610, 1280, and 8700 MHz maps over the same area as we did
for 150 MHz. We note that before measuring the fluxes, we made low-resolution
maps similar to the resolution of the 150 MHz map. Then, we convolved the maps
to the exact resolution as the 150 MHz map. Figure 17 shows the radio spectrum
of the H ii region along with the thermal free-free emission model (Verschuur
& Kellermann, 1988) of the form:

$S_{\nu}=\frac{2k\nu^{2}}{c^{2}}\Omega_{s}T_{e}(1-e^{-\tau_{ff}})$ (3)

where the optical depth, $\tau_{ff}$ is expressed as

$\tau_{ff}=0.082\times\left[\frac{EM}{{\rm
cm^{-6}pc}}\right]\left[\frac{T_{e}}{{\rm
K}}\right]^{-1.35}\left[\frac{\nu}{{\rm GHz}}\right]^{-2.1}.$ (4)

In the above equations, $k$ is the Boltzmann constant, $\nu$ is the frequency,
$c$ is the speed of light in vacuum, $T_{e}$ is the electron temperature, $EM$
is the emission measure, and $\Omega_{s}$ is the source solid angle. Here, we
opted $\Omega_{s}$ to be $\frac{2r\pi}{6}$ for a circular aperture of radius
$r$ (Mezger & Henderson, 1967). The free-free emission model resulted in the
electron temperature $T_{e}\simeq 5700$ $\pm$ 400 K and emission measure
$EM\simeq$3.3$\pm$0.3 $\times 10^{4}$ cm-6 pc. We then estimated the rms
electron density ($n_{e}$) using the relation, $EM$ = $n_{e}^{2}$ $\times$
$l$, where $l$ is the path length and $n_{e}$ is the electron density. This
yields $n_{e}$ $\simeq$ 165 $\pm$ 10 cm-3 using source size as the path
length. We note that these values represent the average properties of the H ii
region over a radius of $\sim$0.7 arcmin, and if the H ii region is clumpy, as
often the case, these values can be higher at peak positions of the clumpy
structures. Nonetheless, we find that our estimates are in agreement with the
electron temperature in the range 0.78 $\pm$ 0.13 to 1.02 $\pm$ 0.07 K
(Fernández-Martín et al., 2017) and electron density in the range 180 $\pm$ 10
to 222 $\pm$ 10 cm-3 obtained by Fernández-Martín et al. (2017) using the
nebular analysis of the optical emission lines.

For optically thin free-free emission, the radio flux density is directly
proportional to the flux of the ionizing photons. And as can be seen from
Figure 17, the H ii region is optically thin at high frequencies. We thus
estimate the total Lyman continuum photons $N_{Lyc}$ emitted per second from
the ionizing star using the total integrated flux $S_{\nu}$ of the H ii region
at 8700 MHz as per the relation given in Rubin (1968)

$N_{Lyc}=4.76\cdot
10^{48}\left(\frac{S_{\nu}}{\textnormal{Jy}}\right)\left(\frac{T_{e}}{\textnormal{K}}\right)^{-0.45}\left(\frac{\nu}{\textnormal{GHz}}\right)^{0.1}\left(\frac{d}{\textnormal{kpc}}\right)^{2}$
(5)

where d is the distance of the region, while the meaning of the other terms
are the same as in Equs. 3 & 4\. Using this relation, we estimate log
($N_{Lyc}$) to be $\simeq$ 47.70.

Figure 18: Image showing the distribution of WISE 12 $\mu$m (background image)
emission and ionized gas emission at 8700 MHz (green contours) of S228. The
red contours show the distribution of cold dust of column density greater than
3 $\times$ 1021 cm-2, while the green contours reflect the 8700 MHz emission
above 0.0005 Jy/beam.

In general, photo-dissociation regions (PDRs) are found at the surface layer
of molecular clouds surrounding the H ii regions. PAH molecules are strong
tracers of PDRs (see Samal et al., 2007, and references therein). In this
regard, WISE band 3 with an effective wavelength of $\sim$12 $\mu$m is a good
tracer of PDR as it contains emission lines of PAH molecules (for details, see
Anderson et al., 2019). We thus consider the bright diffuse 12 $\mu$m emission
around the H ii region coming from the PDR region. As can be seen from Figure
18, the 8700 MHz emission is mainly distributed within the bright PDR,
implying that most of the radio emission is coming primarily from the H ii
region bordered by PDR.

From spectroscopic observations, we know that the effective temperature of the
massive star is $\sim$33000 $\pm$ 1000 K, thus one would expect that the
minimum log($N_{lyc}$) from such a star to be $\simeq$ 48.10 photons per
second (Martins et al., 2005) considering the lower limit of the temperature.
We find that this value is higher than log($N_{Lyc}$) estimated from the 8700
MHz emission, implying that the fraction of the photons could have been leaked
into the ISM along low-density pathways of the H ii region. We discuss this
point further in Section 22.

####  3.2.2 Dust Distribution and Properties

To investigate the physical condition of dust around the S228 region, we
derived column density and dust temperature maps by performing a pixel-to-
pixel modified black-body fit to the 160, 250, 350, and 500 $\mu$m Herschel
images following the procedure outlined in Battersby et al. (2011); Mallick et
al. (2015). Briefly, prior to performing the modified black-body fit, we
converted all the SPIRE images to the PACS flux unit (i.e., Jy pixel-1). Then
we convolved and regridded all the shorter wavelength images to the resolution
and pixel size of the 500 $\mu$m map. Next, we minimize the contribution of
possible excess dust emission from each image along the line-of-sight by
subtracting the corresponding background flux, which we estimated from a field
nearly devoid of emission. Finally, we fitted the modified black-body on these
background-subtracted fluxes. For the spectral fitting, we use a dust spectral
index of $\beta$=2, and the dust opacity per unit mass column density
$\kappa_{\nu}=0.1~{}(\nu/1000~{}{\rm GHz})^{\beta}$ cm2gm-1 as given in
Beckwith & Sargent (1991), keeping the dust temperature Tdust, and the dust
column density $N$(H${}_{2})$ as free parameters.

Figure 19: The left panel shows the dust temperature distribution of the S228
environment along with the distribution of ionized gas (black contours). The
contour levels of the ionized gas are the same as in Figure 16. The warm dusty
lobes and the heated dust of the central parental cloud are also marked. The
middle panel shows the dust column density distribution along with the dust
temperature contours at 17.2, 16.4, 17.6, 18.4, and 19.0 K. Two filamentary
structures attached to the western clump are also marked. The right panel
shows the zoomed view of the western clump. The background image is the
Hershel 160 $\mu$m map and the yellow contours correspond to the dense gas
above column density greater than 3 $\times$ 1021 cm-2. The CUTEX identified
compact sources are labelled as $\\#1$ to $\\#5$.

Figure 19 shows the beam-averaged low-resolution ($\sim$36${\arcsec}$) dust
temperature and (left) dust column density maps (middle) of the S228 complex,
along with the emission at $Herschel$ 160 $\mu$m of the high column density
region. As can be seen from the figure, the temperature of the dust is between
17 and 28 K, and is distributed over a much wider area (size $\sim$10
arcmin$\times$ 20 arcmin) than the size of the cluster (i.e. radius $\sim$2.5
arcmin). The temperature map shows an almost elongated dust distribution
similar to those in bipolar H ii regions (Samal et al., 2018). For example,
similar to bipolar H ii regions, S228 displays two dusty lobes, each with a
size of $\sim$10 arcmin ($\sim$9.6 pc) extending nearly perpendicular to a
faint warm dust lane seen at the base of the lobes. The peak of the
temperature map coincides with the radio continuum emission, implying the
high-temperature zone is primarily created by the intense UV radiation coming
from the cluster. In contrast to the temperature map, the column density map
displays a lower dust column density within the bipolar H ii region, but
exhibits higher column density structures with density in the range 2$-$7
$\times$ 1021 cm-2 in the western part of the H ii region. In particular, in
the immediate vicinity of the H ii region lies a nearly a semicircular clumpy
structure with a radius $\sim$2.8 pc and column density $>$ 3 $\times$ 1021
cm-2. In general, molecular clumps have typical sizes of a few parsecs and are
sites of active star formation. Thus, it could be a site of ongoing star
formation as column densities above $\sim$5 $\times$ 1021 cm-2 are, in
general, observed to be sites of recent star formation (Lada et al., 2010). In
fact, we found four 70/160 $\mu$m point sources within the condensation
affirming the above hypothesis (see Figure 19 right panel). The average dust
temperature of the clump is $\sim$16 K, while the average column density is
$\sim$4 $\times$ 1021 cm-2. The column density map also illustrates that the
clump is associated with two filamentary structures in the north-western
direction, and south-western directions, respectively. The north-western
filament is faint and narrow with a mean temperature around 15.5 K, while the
south-western filament is slightly structured with temperature in the range
14.5$-$15.5 K.

We estimated the total mass ($M_{gas}$) of the clump above column density
$\sim$3 $\times$ 1021 cm-2 using the following equation:

$M=\mu{\mathrm{m}_{H}}A_{\mathrm{p}ix}\Sigma{\mathrm{H}_{2}}\,$ (6)

where $\mu$ is the mean molecular weight, ${\mathrm{m}_{H}}$ is the mass of
the hydrogen atom, $\Sigma$H2 is the integrated H2 column density, and
$A_{\mathrm{p}ix}$ is the area of a pixel in cm-2 at the distance of the
region. The above approach yields area, mass, and density of the clump to be
$\sim$28 pc2, $\sim$2700 M⊙, and $\sim$350 cm-2, respectively. We find that
the properties of the clump are similar to the nearby Ophiuchus star forming
region which is one of the youngest (age $\sim$1 Myr) and closest (distance
$\sim$125 pc) star-forming regions having a size of $\sim$29 pc2 and mass
$\sim$3100 M☉ (Dunham et al., 2015).

The stability of a clump against gravitational collapse can be evaluated using
the virial parameter (Kauffmann et al., 2013)

$\mathit{\alpha}=1.2\left(\frac{\sigma_{\upsilon}}{\rm km\
s^{-1}}\right)^{2}\left(\frac{R_{\rm eff}}{\rm
pc}\right)\left(\frac{M}{10^{3}M_{\odot}}\right)^{-1}$ (7)

where $\sigma_{\upsilon}$ is the one-dimensional velocity dispersion, $R_{\rm
eff}$ is the effective radius, and $M$ is the mass of the clump. In general,
$\alpha$ $<$ 1 is suggestive of collapsing clumps while $\alpha$ $>$ 2 is
suggestive of dissipating clumps and $\alpha$ $\sim$1$-$2 describes a clump
that is in approximate equilibrium. However, the external pressure confined
clumps with $\alpha\leq 2$ are also found to be bound and can live longer with
respect to the dynamical timescale (Bertoldi & McKee, 1992). In the present
case, using $\sigma$ = 1.3 km s-1estimated over clump area from the 13CO map
(discussed in Section 22), we find $\alpha$ $\sim$1.6, implying that clump may
still be bound.

####  3.2.3 Herschel Compact Sources and Properties

From the right panel of Figure 19, it appears that the western clump has been
fragmented into five compact structures (marked with number #1 to #5), four of
which (sources #1 to #4) are protostellar as each of them is associated with a
70/160 $\mu$m point source, while the source #5 is not associated with any
point like source, thus is likely a prestellar source. The presence of 70/160
$\mu$m point sources within column density peaks suggests a fresh star
formation is happening at the western border of the nebula.

In order to understand the properties and evolutionary status of the 160
$\mu$m point sources, we extracted their far-infrared fluxes between 70 and
500 $\mu$m using the CUrvature Thresholding EXtractor (CUTEX) software
described in Molinari et al. (2011). The CUTEX was specifically developed to
optimize the source detection and extraction in the spatially varying
background like the emission seen in the Herschel maps of the star-forming
environments (e.g. Molinari et al., 2011). In order to estimate the envelope
temperatures of the identified point sources, we fitted the observed fluxes at
70, 160, 250, and 350 $\mu$m with the modified blackbody model. Fluxes at 500
$\mu$m have been excluded, owing to the low-resolution of the 500 $\mu$m beam.
This is done in order to avoid bias in the fitting procedure due to the
overestimation of fluxes at 500 $\mu$m because of source confusion and the
inclusion of excess background emission. We also adopted 20 percent error in
flux values instead of formal photometric errors, in order to avoid any
possible bias caused by underestimation of the flux uncertainties. We fitted
the modified blackbody of the form, $S_{\nu}=A\,\nu^{\beta}\,B_{\nu}(T_{\rm
dust})$, where $S_{\nu}$ is the observed flux distribution, $A$ is a scaling
factor, $B_{\nu}(T_{\rm dust})$ is the Planck function for the dust
temperature $T_{\rm dust}$ , and $\beta$ is the dust emissivity spectral
index. A sample SED is shown in Figure 20 for $\beta$=2.

Having derived dust temperature, we then determined the total mass $Mass$ (gas
$+$ dust) of the envelope from the dust continuum flux, $S_{\nu}$, using the
following equation:

${\rm\it Mass}=\frac{S_{\nu}\,Rd^{2}}{\kappa_{\nu}\,B_{\nu}(T_{dust})}$ (8)

where $d$ is the distance, $R$ is the gas-to-dust ratio and is considered to
be 100, and $\kappa_{\nu}$ is the dust mass opacity. We use the same dust
opacity law as used in Section 3.2.2.We also estimated bolometric luminosities
of the sources by integrating SED between 2 and 1000 $\mu$m. We note that,
since we have not taken into account the wavelength dependence of $\beta$,
therefore, the uncertainty in the mass can be of a factor of two, as discussed
in Deharveng et al. (2015). Moreover, if the compact structures contain
multiple point sources that are unresolved at Herschel bands, the derived mass
and luminosity can be even more discrepant. Nonetheless, taking these
properties of the sources at face value, we infer their likely evolutionary
status by plotting them on the M${}_{env}-$ Lbol diagram. Figure 21 shows the
Menv $-$ Lbol diagram of the sources along with the evolutionary tracks of
protostellar objects from André et al. (2008). The figure also marks the zones
of Class 0 and Class I sources. As can be seen, all the sources lie in the
Class 0 zone of the plot and the evolutionary tracks in the plot indicate that
these objects would evolve into stars of the mass range $\sim$3 $-$ 15 M☉.
This implies that the condensation is possibly a site of low- to intermediate-
mass star formation.

##  4 Discussion

Figure 20: The SED of the embedded source #4. The circles denote the observed
flux values. The black solid curve shows the grey-body fit to the data points,
between 70 $\mu$m and 350 $\mu$m.  Figure 21:  The (Lbol, Menv) diagram of the
candidate protostars detected in the western clump (ID numbers are the same as
in Figure 19). The dashed blue lines represent the evolutionary tracks from
André et al. (2008). Evolution proceeds from the upper left to the lower right
(indicated by arrows at the end of each track). The final stellar masses of
these tracks, in solar units, are given above the vertical lines. The slanted
red line corresponds to the location where 50% of the initial core mass is
converted into stellar mass (Bontemps et al., 1996; André et al., 2000).

###  4.1 Gas Removal and Dynamical Status of the Cluster

Stellar feedback plays an important role in the removal of gas from star
clusters, and subsequently cluster members dissolve completely into the
galactic field (Lada & Lada, 2003). It is suggested that by comparing the age
of a star in the cluster with its crossing time ($T_{cr}$) one can distinguish
expanding clusters from bound clusters. According to Gieles & Portegies Zwart
(2011), $\frac{T_{cr}}{Age}\sim 1$, separates bound clusters ($T_{cr}$ $<$
Age) from the unbound associations ($T_{cr}$ $>$ Age). The general definition
of $T_{cr}$ (= 2$R_{H}/\sigma$) includes half mass radius ($R_{H}$) and the
root-mean-square velocity dispersion ($\sigma$) of the member stars (Binney &
Tremaine, 2008). Since we do not have velocity measurements of stars, we thus
use the expression $T_{cr}=2.8({R_{V}^{3}}/{GM})^{1/2}$, to estimate the
crossing time; where $M$ is the total mass of the system, $G$ is the
gravitational constant and is $\simeq$ 0.0045 pc3 M☉-1 Myr-1, and $R_{V}$ is
the virial radius of the cluster (Gieles, 2010; Weidner et al., 2007). The
latter is related to the $R_{H}$ as $R_{V}$ = 1.25$\times R_{H}$. We made an
approximate estimate of the $R_{H}$ from the cluster center as the radius
where the star count above the photometric completeness level is exactly half
of the total number of stars within the cluster radius, and it turns out to be
1.07 pc. We assume that the mass of each star is roughly $\sim$0.5 M☉, based
on the fact thatf the mass distribution of stars in young clusters peaks
somewhere between 0.2 to 0.7 M☉ (Damian et al., 2021). Using this approach, we
estimated $T_{cr}$ to be $\sim$3 Myr, implying that the cluster is probably
marginally bound or in its initial stage of expansion, considering its age
$\sim$3 Myr. It is worth noting that recently Kuhn et al. (2019) studied a
sample of 28 clusters and associations with ages $\sim$1-5 Myr using PM
measurements from Gaia DR2 and revealed that at least 75% of these systems are
expanding.

###  4.2 Comparison to Other Young Clusters

Lada & Lada (2003) examined a sample of young embedded clusters within 2 kpc
from the Sun with deep NIR observations and have tabulated their properties.
We find that IRAS 05100+3723 is more massive than the majority of the nearby
embedded clusters, except the Orion Nebula Cluster (ONC). The ONC is one of
the nearest ($\sim$450 pc), young ($\sim$2 Myr), massive ($>$1000 M☉)
clusters, and hosts four massive stars of spectral type between B0 and O7 (for
details see Panwar et al., 2018, and references therein). Compared to ONC,
IRAS 05100+3723 is a slightly more evolved (age $\sim$3 Myr) and less massive
(mass $\sim$500 M☉) cluster and hosts only a single massive star of spectral
type O8.5. We find that in terms of mass, age, and size, the studied cluster
resembles the cluster Stock 8, studied by Jose et al. (2017). Stock 8 is a
young cluster of age $\sim$3 Myr with the most massive star being a star of
spectral type between O8 and O9 and total stellar mass $\sim$580 M☉. We also
find that IRAS 05100+3723 lies well below the mass-radius relation
($mass\propto r^{1.67}$) given by Pfalzner et al. (2016), derived for embedded
clusters. This could be due to the fact that the cluster is possibly expanding
and dispersing into the Galactic ISM. As a result, the cluster is not compact
anymore, while embedded clusters are, in general, bound and compact systems.
In fact, we find that IRAS 05100+3723 lies between embedded and loose clusters
in the radius-age plane of Pfalzner & Kaczmarek (2013). Although, the total
$A_{\it V}$ in the direction of the cluster is 3.3 mag, but extinction
intrinsic to the cluster is only $A_{V}\sim$1 mag, which also points towards
the fact that the cluster is probably no more an embedded cluster.

###  4.3 Star Formation Processes and Activity in the Complex

Figure 22: The image showing the distribution of 13CO intensity in the gray
scale. The outer boundary of the $Herschel$ dust temperature map is shown with
a yellow contour with $T_{d}$ = 17.2 K. The extent of the cluster is shown
with a red circle. And the $Herschel$ column density contours above density 3
$\times$ 1021 cm-2 (in the direction of western clump) are shown in green. The
contour levels are same as given in the right panel of Figure 19.  Figure 23:
Average 13CO spectrum observed towards the S228 complex. The red and blue
lines indicate the entire velocity range and velocity range associated with
the S228 complex.

####  4.3.1 Cloud Structure, Cluster Formation, and Leaking fraction of the
Ionized Gas

Figure 22 shows the 13CO gas distribution in the complex, along with warm and
cold dust distributions derived from the temperature and column density maps.
The 13CO intensity map was made using the observations taken with the FCRAO
telescope at a spatial resolution of $\sim$45 arcsec and a velocity resolution
$\sim$0.25 km s-1(provided by Mark Heyer, in a private communication). In the
13CO spectrum, two velocity components are found in the direction of S228, as
shown in Figure 23. We obtained the moment maps (i.e. intensity, velocity, and
velocity dispersion maps) of S228 region using its velocity component in the
range $-$13.5 to $-$3.5 km s-1, the velocity range corresponding to S228 (e.g.
Chen et al., 2020). As shown in Figure 22, the distribution of the 13CO
intensity suggests that the cluster lies at the end of a filamentary cloud. It
is generally hypothesized that star-forming clouds collapse to lower-
dimensional structures, producing first sheets and then filaments (Lin et al.,
1965; Burkert & Hartmann, 2004; Gómez & Vázquez-Semadeni, 2014; Naranjo-Romero
et al., 2020). Simulations show that such clouds experience highly non-linear
gravitational acceleration as a function of position, causing the material to
pile up near the cloud edge, forming a young cluster like Orion (e.g. Burkert
& Hartmann, 2004; Hartmann & Burkert, 2007; Heitsch et al., 2008).

From the 13CO moment 1 map, we find that the VLSR of the 13CO molecular gas in
the zone of the ionized gas is $\sim-$5.5 km s-1, while the VLSR of the
ionized gas lies in the range $-$9.4 to $-$13.6 km s-1(Israel, 1977; Chen et
al., 2020). The mean velocity of the ionized gas differs from that of the
molecular gas by 4$-$8 km s-1, implying that the ionizing gas is possibly
streaming away from the cloud. This behavior is typical for H ii regions where
massive stars form
near the very edge of a molecular cloud (Tenorio-Tagle, 1979) or in the center
of a flat or sheet-like cloud (Bodenheimer et al., 1979), resulting in an easy
flow of the ionized gas along the low-density paths of the parental cloud.

Since the morphology of the warm dust is more like the morphology of a bipolar
H ii region, we thus hypothesized that the H ii region might have formed at
the very end of a sheet-like or flattened cloud containing a central filament
as advocated in Deharveng et al. (2015). In such clouds density along the
equatorial axis is expected to be high, whereas it is expected to be low in
the polar directions. Considering that the ionized gas is streaming away from
the filamentary cloud at a minimum velocity of $\sim$5 km s-1, one would
expect that the ionized gas to reach $\sim$15 pc in 3 Myr (i.e the age of the
cluster) from its original location. This is comparable with the projected
size, $\sim$10 pc, of the warm dusty lobes seen in the temperature map. This
also suggests that a fraction of the ionizing photons could have leaked into
the surrounding ISM heating the dust up to several parsecs. Comparing the
Lyman continuum photons expected from the ionizing star of the H ii region
with the observed Lyman continuum photons derived from radio observations
within the bright PDR zone, we find that approximately 60% of the Lyman
photons likely have escaped from the H ii region into the diffuse ISM during
the lifetime of the star. If we consider the uncertainty in the estimation of
temperature and density of the ionized gas, then also the escape fraction is
in the range of 40$-$50%. Our estimated escape fraction is in good agreement
with the values found for other H ii regions (e.g. Oey & Kennicutt, 1997;
Pellegrini et al., 2012). We note, the escape fraction also strongly depends
on the age of the Lyman photon emitting source, and structure and geometry of
the medium (Bodenheimer et al., 1979; Yorke et al., 1982; Howard et al.,
2017); thus, may vary from region to region.

####  4.3.2 Compression and Confinement of Cold Gas, and Formation of Dense
Clump

Figure 22 shows that the western clump (shown by green contours) lies close to
the H ii region. The clump displays bow-like morphology with its apex facing
the H ii region, as found in numerical simulations of H ii regions expanding
into collapsing molecular clouds (e.g. Walch et al., 2015). This suggests that
the over-pressured expanding H ii region possibly has compressed and pushed
the western clump to its present shape. To evaluate the degree of interaction
between the H ii region and the clump, we evaluated various average pressures
within both the regions using the equations given below. We estimated pressure
due to ionized gas of the H ii region using the following relation:

$\begin{split}P_{\mbox{H~{}{\sc ii}~{}}}&=\sqrt{3Q_{\rm H}\over
4\pi\alpha_{rec}r^{3}}kT\\\ &\approx 10^{-9}\,\left(\frac{Q_{\rm H}}{2\times
10^{49}\,\textrm{s}^{-1}}\right)^{1/2}\left(\frac{0.72\,\textrm{pc}}{r}\right)^{3/2}\,\textrm{dyn
cm}^{-2}\,\end{split}$ (9)

where $r$ is the radius, $Q_{\rm H}$ is the Lyman continuum photon responsible
for the ionization of the H ii region, and $\alpha_{rec}$ is the recombination
coefficient (for details see Eq. 6 of Murray, 2009). $Q_{\rm H}$ is taken to
be $\sim$5.1 $\times$ 1047 photons per second, while for the clump it is
assumed to be zero as no hyper or ultra-compact H ii regions present in our
high-resolution 8700 MHz image. We estimated radiation pressure using the
following relation:

$\begin{split}P_{rad}&=L/4\pi cr^{2}\\\ &=4.4\times
10^{-15}\,\left(\frac{L}{\mbox{$L_{\sun}$}}\right)\left(\frac{r}{\textrm{
pc}}\right)^{-2}\,\textrm{dyn cm}^{-2}\,\end{split}$ (10)

where we adopt the ionizing star of the H ii region as the dominant source of
stellar luminosity ($L$), while in the clump the $L_{bol}$ of the most massive
protostar is adopted as a proxy for stellar luminosity. We then estimated the
turbulent pressure using the following relation:

$\begin{split}P_{turb}&=\rho\sigma_{nt}^{2}\\\ &=4.7\times
10^{-14}\,\left(\frac{n}{\textrm{cm}^{-3}}\right)\left(\frac{\sigma_{nt}}{\textrm{km\
s}^{-1}}\right)^{2}\,\textrm{dyn cm}^{-2}\,\end{split}$ (11)

within the H ii region and the clump, where $\rho$ is the mass density, $n$ is
the particle density, and

$\begin{split}\sigma_{\mathrm{nt}}=\sqrt{\sigma_{\mathrm{obs}}^{2}-\sigma_{\mathrm{th}}^{2}}\end{split}$
(12)

is the non-thermal velocity dispersion of the gas. Assuming a Gaussian
distribution of the line profiles, $\sigma_{\mathrm{obs}}$ and
$\sigma_{\mathrm{th}}$ can be estimated from line-widths ($\Delta V$) using

$\sigma_{\mathrm{obs}}=\frac{\Delta V_{obs}}{2.35}\mbox{ and
}\sigma_{\mathrm{th}}=\frac{\Delta V_{th}}{2.35}.$ (13)

For the ionized gas within the H ii region, we use the observed line-width of
the hydrogen radio recombination (RRL) line from Chen et al. (2020), while for
the clump we use the line-width of the 13CO line within the clump area. For
the molecular gas, we use the expression, ${\Delta
V_{th}}=\sqrt{\frac{8\it{ln2}kT}{m_{\mathrm{co}}}}$, where $k$ is the
Boltzmann’s constant, $T$ is the kinetic temperature of the molecular gas, and
$m_{\mathrm{co}}$ is the mass of 13CO molecule in amu. For the ionized gas, we
use the expression, ${\Delta
V_{th}}=21.4\sqrt{\frac{T_{\mathrm{e}}}{10^{4}K}}$, for the hydrogen atom
(Garay & Lizano, 1999), where $T_{\mathrm{e}}$ is the electron temperature.
Lastly, we estimated thermal pressure using the equation:

$\begin{split}P_{them}&=2nkT\\\ &=2.8\times
10^{-16}\,\left(\frac{n_{e}}{\textrm{cm}^{-3}}\right)\left(\frac{T}{K}\right)\,\textrm{dyn
cm}^{-2}\end{split}$ (14)

where we use the mean density and mean temperature of the ionized gas and cold
dust. Doing so, we estimated the total pressure within the ionized region

$P_{ionized}=P_{\mbox{H~{}{\sc
ii}~{}}}+P_{\rm{rad}}+P_{\rm{turb}}+P_{\rm{them}}$ (15)

to be $\sim$4.5 $\times$10-8 dyn cm-2, while the total pressure within the
clump

$P_{\rm clump}=P_{\rm{rad}}+P_{\rm{turb}}+P_{\rm{therm}}$ (16)

to be $\sim$2.3 $\times$10-9 dyn cm-2, implying that the H ii region must
still be compressing the clump, as a result the clump may be under external
pressure confinement. However, since the typical average pressure of the ISM
is in the range of 10-11 $-$ 10-12 dyn cm-2 (Bloemen, 1987; Draine, 2011);
thus, we hypothesized that the H ii region must be expanding more rapidly into
the ISM. In the present case, the expansion may be occurring more
preferentially in the direction perpendicular to the plane of the cloud, as a
result, we are observing warm dusty bipolar lobes.

Figure 24: Position-velocity (PV) maps along the long axis of the L-shaped
filament. The left panel shows the 13CO intensity map of the filament in
Galactic longitude and latitude coordinates, the middle panel shows the PV map
of the P1$-$P2 filament, while the right panel shows the PV map of the P2$-$P3
filament.

Herschel column density map shows (see Section 3.2.2) that the clump is
located at the junction of two filamentary structures, while in the large-
scale 13CO map, the clump seems to be located at the end of a long L-shaped
filamentary structure. This long filamentary structure corresponds to the
south-western filament seen in the Herschel image. The non-visibility of the
small north-western filament in the 13CO map could be due to the lower
sensitivity of the 13CO map. We note that the small-scale filamentary
structures can be generated due to the self-gravity of the clump. Nonetheless,
the situation is very similar to several other star-forming regions where
massive clumps have been found at the merger or convergence point of filaments
(e.g. Myers, 2009; Schneider et al., 2012; Kumar et al., 2020) or at the end
of a large-scale filament due to edge collapse (e.g. Burkert & Hartmann, 2004;
Pon et al., 2011; Yuan et al., 2020). The large-scale velocity gradients along
the filaments have often been interpreted as signatures of mass flow towards
star-forming clumps as a consequence of the longitudinal collapse of the
filaments (Kirk et al., 2013; Ryabukhina et al., 2018; Dutta et al., 2018).
Although the structure of the filament is not very smooth, which could be due
to star-formation activity at multiple locations of the filament as the
filament is presumably older than 3 Myr (i.e. the age of the cluster),
nonetheless, we search for signatures of underlying large-scale flow (i.e.
signatures of velocity gradient) along the filament’s long axis in the
position-velocity (PV) map. Figure 24 shows the PV maps of the filament,
extracted along its spine. To extract the PV maps, we divide the L$-$shaped
filament into two parts (P1$-$P2 and P2$-$P3) as marked in Fig 24 (left
panel). Figure 24 (middle panel) and Figure 24 (right panel), show the PV maps
of P1$-$P2, and P2$-$P3, respectively. In PV maps, the velocity gradient in
P1$-$P2 is weaker compared to the one observed for the P2$-$P3 region.
Overall, the velocity gradient in the whole filament is $\sim$0.05 km s-1.
This weak velocity gradient could be due to the fact that the filament, being
$\sim$3 Myr old (cluster age), star formation along the filament has already
distorted its gas kinematics and also has changed the location of star-forming
potential; thus, the kinematics at smaller-scale during its evolution (e.g.
see discussions in Peretto et al., 2014). Nonetheless, the velocity gradient
(i.e $\sim$0.1 km s-1pc-1) observed within P2$-$P3 is comparable to some of
the large-scale filaments such as IRDC G035.39$-$00.33 ($\sim$0.2 km s-1pc-1;
Sokolov et al., 2017) and W33 filamentary system (0.3$-$0.1 km s-1pc-1; Liu et
al., 2021). This points to the fact that the filament has likely been
dynamically active for a few Myr, thus might have supplied cold matter to the
cluster location. However, high-resolution spectral observations of the
filament close to the clump location will be essential to better understand
the filamentary flow.

####  4.3.3 Second Generation Star Formation

In the filamentary environment, numerical simulations by Fukuda & Hanawa
(2000) suggest that the expansion of H ii region can generate sequential waves
of star-forming cores along the long axis of the filament on either side of
the H ii region. This has particularly been observed in bipolar H ii regions,
which are thought to be formed due to anisotropic expansion of the H ii region
in a flat or sheet-like cloud containing filaments (Deharveng et al., 2015;
Samal et al., 2018). Indeed, Samal et al. (2018), from the analysis of a
sample of bipolar bubbles found that the most massive and compact clumps with
signatures of massive star formation are always located at the waist of the
bipolar bubbles and they argue that these massive clumps are the possible
sites of second-generation massive- to moderate-mass star formation. Eswaraiah
et al. (2019) using magnetic field geometry, strength, and comparing various
pressure components, showed that the evolution and star formation of the
clumps at the waists of bipolar H ii regions are indeed strongly influenced by
the H ii region feedback.

The morphology of the S228 in WISE 12 $\mu$m and Herschel temperature map
appears to be bipolar with two lobes extending nearly perpendicular to a faint
dust lane located at the bases of the lobes. At the western waist of the
bubble lies a clump whose mean temperature and mean column density are 16 K
and $\sim$4 $\times$ 1021 cm-2, respectively, which are conducive for the
process of star formation (Lada et al., 2010; Eden et al., 2019).

Within this dense clump, as discussed in Section 3.2.3, several Class 0/I
protostars and a starless core, have been identified. The fact that the age of
Class 0/I sources is of the order of $\sim$105 yrs (Evans et al., 2009), and
these sources are located in a clump that lies at the junction point of the H
ii region and filament, and the clump is under the influence of a $\sim$3 Myr
old H ii region, altogether suggest that these protostars are the likley
second generation stars of the complex.

##  5 Summary

In order to understand the formation of young massive clusters and their
feedback effects on the parental cloud, we investigate the young cluster IRAS
05100+3723 and studied its environment using multiwavelength data sets.

Our findings conclude that IRAS 05100+3723 is an intermediate-mass (mass
$\sim$500 M☉) young cluster formed around 3 Myr ago at the very end of a long
filamentary cloud. We find that the massive star of the cluster has created an
H ii region of size $\sim$2.7 pc and temperature $\sim$5,700 K. However, it
has heated the dust up to several parsecs and the distribution of the warm
dust on a large-scale resembles a bipolar H ii regions. This implies that the
parental cloud could be sheet-like or flattened in nature containing a central
filament as suggested by Deharveng et al. (2015) for molecular clouds that
host bipolar H ii regions.

Although, high-resolution kinematic studies of the filament are needed,
nonetheless, from the evidences found in Sects. 4.3.1 and 4.3.2, we
hypothesized that the formation of the cluster (and the H ii region) is likely
due to the edge or end-dominated global collapse of the filament as advocated
in Burkert & Hartmann (2004); Pon et al. (2011) and then the formation of the
western clump followed. We suggest that the latter is either induced or
facilitated by the compression of the expanding H ii region (Sect. 4.3.2) onto
the inflowing filamentary material.

Inside the clump, we observed several far-infrared point sources of class 0/I
nature. We suggest that these sources are the second-generation stars of the
complex as such sources are absent in the vicinity of the ionizing star of the
H ii region (see Sect. 3.2.3), they are significantly younger (age $\sim$ 105
yr) than age of the H ii region (age $\sim$ 3 Myr), and they occupy a distinct
location (i.e. at the interaction zone of the H ii region and filament)
compared to optically visible stars. We hypothesize this scenario may be
applicable to star formation at the border of several H ii region - filament
environments and may be an efficient process for forming second-generation
stars in molecular clouds. Future high-resolution studies of a larger sample
of young H ii region - filament environments would be helpful to support our
hypothesis.

We thank the anonymous referee for providing valuable comments and suggestions
that improved the paper. This paper, in part, is based on observations made
with MRES mounted on TNT at the Thai National Observatory (program ID
C06$\\_$024). TNT is operated by the National Astronomical Research Institute
of Thailand (Public Organization). We acknowledge Mark Heyer for sharing FCRAO
13CO observations. This research has made use of the SIMBAD database, operated
at CDS, Strasbourg, France. The Gaia space mission is operated by the European
Space Agency (ESA). This publication uses data from the UKIDSS. This work, in
part, uses the data from the Pan-STARRS1 (PS1) surveys. We acknowledge the
data obtained as part of the INT Photometric H$\alpha$ Survey of the Northern
Galactic Plane (IPHAS). This research uses the data obtained with the Spitzer
Space Telescope. The GMRT is run by the National Centre for Radio Astrophysics
of the Tata Institute of Fundamental Research. The National Radio Astronomy
Observatory is a facility of the National Science Foundation operated under
cooperative agreement by Associated Universities, Inc. This work has been
funded by Indo-Thai project, which is supported by Ministry of Higher
Education, Science, Research and Innovation (MHESI), Thailand and Department
of Science and Technology (DST), India (project No. DST/INT/Thai/P-15/2019).
AZ thanks the support of the Institut Universitaire de France. DKO
acknowledges the support of the Department of Atomic Energy, Government of
India (project No. RTI 4002). SP acknowledges the DST-INSPIRE fellowship (No.
IF180092) of the Department of Science and Technology, India.

IPS (van Moorsel et al., 1996), CASA (McMullin et al., 2007), APLpy
(Robitaille & Bressert, 2012), Astropy (Astropy Collaboration et al., 2013),
CUTEX (Molinari et al., 2011), DS9 (Joye & Mandel, 2003; Smithsonian
Astrophysical Observatory, 2000), IRAF (Tody, 1986, 1993), isochrones (Morton,
2015), STARLINK (Currie et al., 2014).

## References

  * Alam et al. (2015) Alam, S., Albareti, F. D., Allende Prieto, C., et al. 2015, ApJS, 219, 12, doi: 10.1088/0067-0049/219/1/12
  * Anderson et al. (2019) Anderson, L. D., Makai, Z., Luisi, M., et al. 2019, ApJ, 882, 11, doi: 10.3847/1538-4357/ab1c59
  * André et al. (2000) André, P., Ward-Thompson, D., & Barsony, M. 2000, in Protostars and Planets IV, ed. V. Mannings, A. P. Boss, & S. S. Russell, 59.  https://arxiv.org/abs/astro-ph/9903284
  * André et al. (2008) André, P., Minier, V., Gallais, P., et al. 2008, A&A, 490, L27, doi: 10.1051/0004-6361:200810957
  * Ascenso et al. (2007) Ascenso, J., Alves, J., Beletsky, Y., & Lago, M. T. V. T. 2007, A&A, 466, 137, doi: 10.1051/0004-6361:20066433
  * Astropy Collaboration et al. (2013) Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al. 2013, A&A, 558, A33, doi: 10.1051/0004-6361/201322068
  * Bailer-Jones (2015) Bailer-Jones, C. A. L. 2015, PASP, 127, 994, doi: 10.1086/683116
  * Bailer-Jones et al. (2018) Bailer-Jones, C. A. L., Rybizki, J., Fouesneau, M., Mantelet, G., & Andrae, R. 2018, AJ, 156, 58, doi: 10.3847/1538-3881/aacb21
  * Balser et al. (2011) Balser, D. S., Rood, R. T., Bania, T. M., & Anderson, L. D. 2011, ApJ, 738, 27, doi: 10.1088/0004-637X/738/1/27
  * Banerjee & Kroupa (2015) Banerjee, S., & Kroupa, P. 2015, MNRAS, 447, 728, doi: 10.1093/mnras/stu2445
  * Banerjee & Kroupa (2017) —. 2017, A&A, 597, A28, doi: 10.1051/0004-6361/201526928
  * Barentsen et al. (2011) Barentsen, G., Vink, J. S., Drew, J. E., et al. 2011, MNRAS, 415, 103, doi: 10.1111/j.1365-2966.2011.18674.x
  * Barentsen et al. (2014) Barentsen, G., Farnhill, H. J., Drew, J. E., et al. 2014, MNRAS, 444, 3230, doi: 10.1093/mnras/stu1651
  * Battersby et al. (2011) Battersby, C., Bally, J., Ginsburg, A., et al. 2011, A&A, 535, A128, doi: 10.1051/0004-6361/201116559
  * Beckwith & Sargent (1991) Beckwith, S. V. W., & Sargent, A. I. 1991, ApJ, 381, 250, doi: 10.1086/170646
  * Bertoldi & McKee (1992) Bertoldi, F., & McKee, C. F. 1992, ApJ, 395, 140, doi: 10.1086/171638
  * Bessell & Brett (1988) Bessell, M. S., & Brett, J. M. 1988, PASP, 100, 1134, doi: 10.1086/132281
  * Bica et al. (2003) Bica, E., Dutra, C. M., & Barbuy, B. 2003, A&A, 397, 177, doi: 10.1051/0004-6361:20021479
  * Binney & Tremaine (2008) Binney, J., & Tremaine, S. 2008, Galactic Dynamics: Second Edition (Princeton University Press)
  * Bloemen (1987) Bloemen, J. B. G. M. 1987, ApJ, 322, 694, doi: 10.1086/165765
  * Bodenheimer et al. (1979) Bodenheimer, P., Tenorio-Tagle, G., & Yorke, H. W. 1979, ApJ, 233, 85, doi: 10.1086/157368
  * Bonnell et al. (2004) Bonnell, I. A., Vine, S. G., & Bate, M. R. 2004, MNRAS, 349, 735, doi: 10.1111/j.1365-2966.2004.07543.x
  * Bontemps et al. (1996) Bontemps, S., Andre, P., Terebey, S., & Cabrit, S. 1996, A&A, 311, 858
  * Borissova et al. (2003) Borissova, J., Pessev, P., Ivanov, V. D., et al. 2003, A&A, 411, 83, doi: 10.1051/0004-6361:20034009
  * Burkert & Hartmann (2004) Burkert, A., & Hartmann, L. 2004, ApJ, 616, 288, doi: 10.1086/424895
  * Chambers et al. (2016) Chambers, K. C., Magnier, E. A., Metcalfe, N., et al. 2016, arXiv e-prints, arXiv:1612.05560.  https://arxiv.org/abs/1612.05560
  * Chen et al. (2020) Chen, H.-Y., Chen, X., Wang, J.-Z., Shen, Z.-Q., & Yang, K. 2020, ApJS, 248, 3, doi: 10.3847/1538-4365/ab818e
  * Chini & Wink (1984) Chini, R., & Wink, J. E. 1984, A&A, 139, L5
  * Comerón & Pasquali (2005) Comerón, F., & Pasquali, A. 2005, A&A, 430, 541, doi: 10.1051/0004-6361:20041788
  * Currie et al. (2014) Currie, M. J., Berry, D. S., Jenness, T., et al. 2014, in Astronomical Society of the Pacific Conference Series, Vol. 485, Astronomical Data Analysis Software and Systems XXIII, ed. N. Manset & P. Forshay, 391
  * Da Rio et al. (2010) Da Rio, N., Robberto, M., Soderblom, D. R., et al. 2010, ApJ, 722, 1092, doi: 10.1088/0004-637X/722/2/1092
  * Damian et al. (2021) Damian, B., Jose, J., Samal, M. R., et al. 2021, arXiv e-prints, arXiv:2101.08804.  https://arxiv.org/abs/2101.08804
  * Das et al. (2021) Das, S. R., Jose, J., Samal, M. R., Zhang, S., & Panwar, N. 2021, MNRAS, 500, 3123, doi: 10.1093/mnras/staa3222
  * Deharveng et al. (2010) Deharveng, L., Schuller, F., Anderson, L. D., et al. 2010, A&A, 523, A6, doi: 10.1051/0004-6361/201014422
  * Deharveng et al. (2015) Deharveng, L., Zavagno, A., Samal, M. R., et al. 2015, A&A, 582, A1, doi: 10.1051/0004-6361/201423835
  * Dotter (2016) Dotter, A. 2016, ApJS, 222, 8, doi: 10.3847/0067-0049/222/1/8
  * Draine (2011) Draine, B. T. 2011, Physics of the Interstellar and Intergalactic Medium (Princeton University Press)
  * Drew et al. (2005) Drew, J. E., Greimel, R., Irwin, M. J., et al. 2005, MNRAS, 362, 753, doi: 10.1111/j.1365-2966.2005.09330.x
  * Dunham et al. (2015) Dunham, M. M., Allen, L. E., Evans, Neal J., I., et al. 2015, ApJS, 220, 11, doi: 10.1088/0067-0049/220/1/11
  * Dutta et al. (2015) Dutta, S., Mondal, S., Jose, J., et al. 2015, MNRAS, 454, 3597, doi: 10.1093/mnras/stv2190
  * Dutta et al. (2018) Dutta, S., Mondal, S., Samal, M. R., & Jose, J. 2018, ApJ, 864, 154, doi: 10.3847/1538-4357/aadb3e
  * Eden et al. (2019) Eden, D. J., Liu, T., Kim, K.-T., et al. 2019, MNRAS, 485, 2895, doi: 10.1093/mnras/stz574
  * Elmegreen & Lada (1977) Elmegreen, B. G., & Lada, C. J. 1977, ApJ, 214, 725, doi: 10.1086/155302
  * Eswaraiah et al. (2019) Eswaraiah, C., Lai, S.-P., Ma, Y., et al. 2019, ApJ, 875, 64, doi: 10.3847/1538-4357/ab0a0c
  * Evans et al. (2009) Evans, Neal J., I., Dunham, M. M., Jørgensen, J. K., et al. 2009, ApJS, 181, 321, doi: 10.1088/0067-0049/181/2/321
  * Fernández-Martín et al. (2017) Fernández-Martín, A., Pérez-Montero, E., Vílchez, J. M., & Mampaso, A. 2017, A&A, 597, A84, doi: 10.1051/0004-6361/201628423
  * Feroz et al. (2009) Feroz, F., Hobson, M. P., & Bridges, M. 2009, MNRAS, 398, 1601, doi: 10.1111/j.1365-2966.2009.14548.x
  * Fukuda & Hanawa (2000) Fukuda, N., & Hanawa, T. 2000, ApJ, 533, 911, doi: 10.1086/308701
  * Gaia Collaboration et al. (2020) Gaia Collaboration, Brown, A. G. A., Vallenari, A., et al. 2020, arXiv e-prints, arXiv:2012.01533.  https://arxiv.org/abs/2012.01533
  * Gaia Collaboration et al. (2016) Gaia Collaboration, Prusti, T., de Bruijne, J. H. J., et al. 2016, A&A, 595, A1, doi: 10.1051/0004-6361/201629272
  * Gaia Collaboration et al. (2018) Gaia Collaboration, Brown, A. G. A., Vallenari, A., et al. 2018, A&A, 616, A1, doi: 10.1051/0004-6361/201833051
  * Garay & Lizano (1999) Garay, G., & Lizano, S. 1999, PASP, 111, 1049, doi: 10.1086/316416
  * Gieles (2010) Gieles, M. 2010, in IAU Symposium, Vol. 266, Star Clusters: Basic Galactic Building Blocks Throughout Time and Space, ed. R. de Grijs & J. R. D. Lépine, 69–80, doi: 10.1017/S1743921309990895
  * Gieles & Portegies Zwart (2011) Gieles, M., & Portegies Zwart, S. F. 2011, MNRAS, 410, L6, doi: 10.1111/j.1745-3933.2010.00967.x
  * Gómez & Vázquez-Semadeni (2014) Gómez, G. C., & Vázquez-Semadeni, E. 2014, ApJ, 791, 124, doi: 10.1088/0004-637X/791/2/124
  * Gutermuth et al. (2009) Gutermuth, R. A., Megeath, S. T., Myers, P. C., et al. 2009, ApJS, 184, 18, doi: 10.1088/0067-0049/184/1/18
  * Gutermuth et al. (2005) Gutermuth, R. A., Megeath, S. T., Pipher, J. L., et al. 2005, ApJ, 632, 397, doi: 10.1086/432460
  * Harayama et al. (2008) Harayama, Y., Eisenhauer, F., & Martins, F. 2008, ApJ, 675, 1319, doi: 10.1086/524650
  * Hartmann & Burkert (2007) Hartmann, L., & Burkert, A. 2007, ApJ, 654, 988, doi: 10.1086/509321
  * Heiter et al. (2002) Heiter, U., Kupka, F., van’t Veer-Menneret, C., et al. 2002, A&A, 392, 619, doi: 10.1051/0004-6361:20020788
  * Heitsch et al. (2008) Heitsch, F., Hartmann, L. W., Slyz, A. D., Devriendt, J. E. G., & Burkert, A. 2008, ApJ, 674, 316, doi: 10.1086/523697
  * Hillenbrand (1997) Hillenbrand, L. A. 1997, AJ, 113, 1733, doi: 10.1086/118389
  * Howard et al. (2017) Howard, C., Pudritz, R., & Klessen, R. 2017, ApJ, 834, 40, doi: 10.3847/1538-4357/834/1/40
  * Hubeny & Lanz (2011) Hubeny, I., & Lanz, T. 2011, Synspec: General Spectrum Synthesis Program.  http://ascl.net/1109.022
  * Hunter & Massey (1990) Hunter, D. A., & Massey, P. 1990, AJ, 99, 846, doi: 10.1086/115378
  * Intema et al. (2017) Intema, H. T., Jagannathan, P., Mooley, K. P., & Frail, D. A. 2017, A&A, 598, A78, doi: 10.1051/0004-6361/201628536
  * Israel (1977) Israel, F. P. 1977, A&A, 60, 233
  * Jackson et al. (2006) Jackson, J. M., Rathborne, J. M., Shah, R. Y., et al. 2006, ApJS, 163, 145, doi: 10.1086/500091
  * Jose et al. (2017) Jose, J., Herczeg, G. J., Samal, M. R., Fang, Q., & Panwar, N. 2017, ApJ, 836, 98, doi: 10.3847/1538-4357/836/1/98
  * Joye & Mandel (2003) Joye, W. A., & Mandel, E. 2003, in Astronomical Society of the Pacific Conference Series, Vol. 295, Astronomical Data Analysis Software and Systems XII, ed. H. E. Payne, R. I. Jedrzejewski, & R. N. Hook, 489
  * Kauffmann et al. (2013) Kauffmann, J., Pillai, T., & Zhang, Q. 2013, ApJ, 765, L35, doi: 10.1088/2041-8205/765/2/L35
  * Kharchenko et al. (2013) Kharchenko, N. V., Piskunov, A. E., Schilbach, E., Röser, S., & Scholz, R. D. 2013, A&A, 558, A53, doi: 10.1051/0004-6361/201322302
  * King (1962) King, I. 1962, AJ, 67, 471, doi: 10.1086/108756
  * Kirk et al. (2013) Kirk, H., Myers, P. C., Bourke, T. L., et al. 2013, ApJ, 766, 115, doi: 10.1088/0004-637X/766/2/115
  * Kroupa (2001) Kroupa, P. 2001, MNRAS, 322, 231, doi: 10.1046/j.1365-8711.2001.04022.x
  * Kuhn et al. (2019) Kuhn, M. A., Hillenbrand, L. A., Sills, A., Feigelson, E. D., & Getman, K. V. 2019, ApJ, 870, 32, doi: 10.3847/1538-4357/aaef8c
  * Kumar et al. (2020) Kumar, M. S. N., Palmeirim, P., Arzoumanian, D., & Inutsuka, S. I. 2020, A&A, 642, A87, doi: 10.1051/0004-6361/202038232
  * Lada & Adams (1992) Lada, C. J., & Adams, F. C. 1992, ApJ, 393, 278, doi: 10.1086/171505
  * Lada & Lada (2003) Lada, C. J., & Lada, E. A. 2003, ARA&A, 41, 57, doi: 10.1146/annurev.astro.41.011802.094844
  * Lada et al. (2010) Lada, C. J., Lombardi, M., & Alves, J. F. 2010, ApJ, 724, 687, doi: 10.1088/0004-637X/724/1/687
  * Lahulla (1985) Lahulla, J. F. 1985, A&AS, 61, 537
  * Lanz & Hubeny (2003) Lanz, T., & Hubeny, I. 2003, ApJS, 146, 417, doi: 10.1086/374373
  * Lawrence et al. (2007) Lawrence, A., Warren, S. J., Almaini, O., et al. 2007, MNRAS, 379, 1599, doi: 10.1111/j.1365-2966.2007.12040.x
  * Lin et al. (1965) Lin, C. C., Mestel, L., & Shu, F. H. 1965, ApJ, 142, 1431, doi: 10.1086/148428
  * Liu et al. (2021) Liu, X.-L., Xu, J.-L., Wang, J.-J., et al. 2021, A&A, 646, A137, doi: 10.1051/0004-6361/201935035
  * Longmore et al. (2014) Longmore, S. N., Kruijssen, J. M. D., Bastian, N., et al. 2014, in Protostars and Planets VI, ed. H. Beuther, R. S. Klessen, C. P. Dullemond, & T. Henning, 291, doi: 10.2458/azu_uapress_9780816531240-ch013
  * Lucas et al. (2008) Lucas, P. W., Hoare, M. G., Longmore, A., et al. 2008, MNRAS, 391, 136, doi: 10.1111/j.1365-2966.2008.13924.x
  * Mallick et al. (2013) Mallick, K. K., Kumar, M. S. N., Ojha, D. K., et al. 2013, ApJ, 779, 113, doi: 10.1088/0004-637X/779/2/113
  * Mallick et al. (2015) Mallick, K. K., Ojha, D. K., Tamura, M., et al. 2015, MNRAS, 447, 2307, doi: 10.1093/mnras/stu2584
  * Martins et al. (2005) Martins, F., Schaerer, D., & Hillier, D. J. 2005, A&A, 436, 1049, doi: 10.1051/0004-6361:20042386
  * McMullin et al. (2007) McMullin, J. P., Waters, B., Schiebel, D., Young, W., & Golap, K. 2007, in Astronomical Society of the Pacific Conference Series, Vol. 376, Astronomical Data Analysis Software and Systems XVI, ed. R. A. Shaw, F. Hill, & D. J. Bell, 127
  * Mège et al. (2021) Mège, P., Russeil, D., Zavagno, A., et al. 2021, A&A, 646, A74, doi: 10.1051/0004-6361/202038956
  * Mezger & Henderson (1967) Mezger, P. G., & Henderson, A. P. 1967, ApJ, 147, 471, doi: 10.1086/149030
  * Minniti et al. (2010) Minniti, D., Lucas, P. W., Emerson, J. P., et al. 2010, New Astronomy, 15, 433, doi: 10.1016/j.newast.2009.12.002
  * Molinari et al. (2011) Molinari, S., Schisano, E., Faustini, F., et al. 2011, A&A, 530, A133, doi: 10.1051/0004-6361/201014752
  * Molinari et al. (2010) Molinari, S., Swinyard, B., Bally, J., et al. 2010, A&A, 518, L100, doi: 10.1051/0004-6361/201014659
  * Morton (2015) Morton, T. D. 2015, isochrones: Stellar model grid package.  http://ascl.net/1503.010
  * Motte et al. (2018) Motte, F., Bontemps, S., & Louvet, F. 2018, ARA&A, 56, 41, doi: 10.1146/annurev-astro-091916-055235
  * Murray (2009) Murray, N. 2009, ApJ, 691, 946, doi: 10.1088/0004-637X/691/2/946
  * Myers (2009) Myers, P. C. 2009, ApJ, 700, 1609, doi: 10.1088/0004-637X/700/2/1609
  * Naranjo-Romero et al. (2020) Naranjo-Romero, R., Vázquez-Semadeni, E., & Loughnane, R. M. 2020, arXiv e-prints, arXiv:2012.12819.  https://arxiv.org/abs/2012.12819
  * Neichel et al. (2015) Neichel, B., Samal, M. R., Plana, H., et al. 2015, A&A, 576, A110, doi: 10.1051/0004-6361/201425464
  * Oey & Kennicutt (1997) Oey, M. S., & Kennicutt, R. C., J. 1997, MNRAS, 291, 827, doi: 10.1093/mnras/291.4.827
  * Panwar et al. (2018) Panwar, N., Pandey, A. K., Samal, M. R., et al. 2018, AJ, 155, 44, doi: 10.3847/1538-3881/aa9f1b
  * Panwar et al. (2019) Panwar, N., Samal, M. R., Pandey, A. K., Singh, H. P., & Sharma, S. 2019, AJ, 157, 112, doi: 10.3847/1538-3881/aafbe6
  * Patten et al. (2006) Patten, B. M., Stauffer, J. R., Burrows, A., et al. 2006, ApJ, 651, 502, doi: 10.1086/507264
  * Pecaut & Mamajek (2013) Pecaut, M. J., & Mamajek, E. E. 2013, ApJS, 208, 9, doi: 10.1088/0067-0049/208/1/9
  * Pellegrini et al. (2012) Pellegrini, E. W., Oey, M. S., Winkler, P. F., et al. 2012, ApJ, 755, 40, doi: 10.1088/0004-637X/755/1/40
  * Peretto et al. (2014) Peretto, N., Fuller, G. A., André, P., et al. 2014, A&A, 561, A83, doi: 10.1051/0004-6361/201322172
  * Pfalzner & Kaczmarek (2013) Pfalzner, S., & Kaczmarek, T. 2013, A&A, 559, A38, doi: 10.1051/0004-6361/201322134
  * Pfalzner et al. (2016) Pfalzner, S., Kirk, H., Sills, A., et al. 2016, A&A, 586, A68, doi: 10.1051/0004-6361/201527449
  * Pilbratt et al. (2010) Pilbratt, G. L., Riedinger, J. R., Passvogel, T., et al. 2010, A&A, 518, L1, doi: 10.1051/0004-6361/201014759
  * Pon et al. (2011) Pon, A., Johnstone, D., & Heitsch, F. 2011, ApJ, 740, 88, doi: 10.1088/0004-637X/740/2/88
  * Preibisch & Mamajek (2008) Preibisch, T., & Mamajek, E. 2008, The Nearest OB Association: Scorpius-Centaurus (Sco OB2), ed. B. Reipurth, Vol. 5, 235
  * Rieke & Lebofsky (1985) Rieke, G. H., & Lebofsky, M. J. 1985, ApJ, 288, 618, doi: 10.1086/162827
  * Robitaille & Bressert (2012) Robitaille, T., & Bressert, E. 2012, APLpy: Astronomical Plotting Library in Python.  http://ascl.net/1208.017
  * Rubin (1968) Rubin, R. H. 1968, ApJ, 154, 391, doi: 10.1086/149766
  * Ryabukhina et al. (2018) Ryabukhina, O. L., Zinchenko, I. I., Samal, M. R., et al. 2018, Research in Astronomy and Astrophysics, 18, 095, doi: 10.1088/1674-4527/18/8/95
  * Salpeter (1955) Salpeter, E. E. 1955, ApJ, 121, 161, doi: 10.1086/145971
  * Samal et al. (2018) Samal, M. R., Deharveng, L., Zavagno, A., et al. 2018, A&A, 617, A67, doi: 10.1051/0004-6361/201833015
  * Samal et al. (2007) Samal, M. R., Pandey, A. K., Ojha, D. K., et al. 2007, ApJ, 671, 555, doi: 10.1086/522941
  * Samal et al. (2010) —. 2010, ApJ, 714, 1015, doi: 10.1088/0004-637X/714/2/1015
  * Samal et al. (2015) Samal, M. R., Ojha, D. K., Jose, J., et al. 2015, A&A, 581, A5, doi: 10.1051/0004-6361/201322787
  * Schneider et al. (2012) Schneider, N., Csengeri, T., Hennemann, M., et al. 2012, A&A, 540, L11, doi: 10.1051/0004-6361/201118566
  * Sharpless (1959) Sharpless, S. 1959, ApJS, 4, 257, doi: 10.1086/190049
  * Sills et al. (2018) Sills, A., Rieder, S., Scora, J., McCloskey, J., & Jaffa, S. 2018, MNRAS, 477, 1903, doi: 10.1093/mnras/sty681
  * Smith et al. (2010) Smith, N., Povich, M. S., Whitney, B. A., et al. 2010, MNRAS, 406, 952, doi: 10.1111/j.1365-2966.2010.16792.x
  * Smithsonian Astrophysical Observatory (2000) Smithsonian Astrophysical Observatory. 2000, SAOImage DS9: A utility for displaying astronomical images in the X11 window environment.  http://ascl.net/0003.002
  * Sokolov et al. (2017) Sokolov, V., Wang, K., Pineda, J. E., et al. 2017, A&A, 606, A133, doi: 10.1051/0004-6361/201630350
  * Swarup et al. (1991) Swarup, G., Ananthakrishnan, S., Kapahi, V. K., et al. 1991, Current Science, 60, 95
  * Tenorio-Tagle (1979) Tenorio-Tagle, G. 1979, A&A, 71, 59
  * Tody (1986) Tody, D. 1986, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 627, Instrumentation in astronomy VI, ed. D. L. Crawford, 733, doi: 10.1117/12.968154
  * Tody (1993) Tody, D. 1993, in Astronomical Society of the Pacific Conference Series, Vol. 52, Astronomical Data Analysis Software and Systems II, ed. R. J. Hanisch, R. J. V. Brissenden, & J. Barnes, 173
  * van Moorsel et al. (1996) van Moorsel, G., Kemball, A., & Greisen, E. 1996, in Astronomical Society of the Pacific Conference Series, Vol. 101, Astronomical Data Analysis Software and Systems V, ed. G. H. Jacoby & J. Barnes, 37
  * Vázquez-Semadeni et al. (2019) Vázquez-Semadeni, E., Palau, A., Ballesteros-Paredes, J., Gómez, G. C., & Zamora-Avilés, M. 2019, MNRAS, 490, 3061, doi: 10.1093/mnras/stz2736
  * Verschuur & Kellermann (1988) Verschuur, G. L., & Kellermann, K. I. 1988, Galactic and extra-galactic radio astronomy (Springer)
  * Walborn & Fitzpatrick (1990) Walborn, N. R., & Fitzpatrick, E. L. 1990, PASP, 102, 379, doi: 10.1086/132646
  * Walch et al. (2015) Walch, S., Whitworth, A. P., Bisbas, T. G., Hubber, D. A., & Wünsch, R. 2015, MNRAS, 452, 2794, doi: 10.1093/mnras/stv1427
  * Weidner et al. (2010) Weidner, C., Kroupa, P., & Bonnell, I. A. D. 2010, MNRAS, 401, 275, doi: 10.1111/j.1365-2966.2009.15633.x
  * Weidner et al. (2007) Weidner, C., Kroupa, P., Nürnberger, D. E. A., & Sterzik, M. F. 2007, MNRAS, 376, 1879, doi: 10.1111/j.1365-2966.2007.11580.x
  * Whitney & GLIMPSE360 Team (2009) Whitney, B., & GLIMPSE360 Team. 2009, in American Astronomical Society Meeting Abstracts, Vol. 214, American Astronomical Society Meeting Abstracts #214, 210.01
  * Williams & Cieza (2011) Williams, J. P., & Cieza, L. A. 2011, ARA&A, 49, 67, doi: 10.1146/annurev-astro-081710-102548
  * Wright et al. (2010) Wright, E. L., Eisenhardt, P. R. M., Mainzer, A. K., et al. 2010, AJ, 140, 1868, doi: 10.1088/0004-6256/140/6/1868
  * Yadav et al. (2016) Yadav, R. K., Pandey, A. K., Sharma, S., et al. 2016, MNRAS, 461, 2502, doi: 10.1093/mnras/stw1356
  * Yorke et al. (1982) Yorke, H. W., Bodenheimer, P., & Tenorio-Tagle, G. 1982, A&A, 108, 25
  * Yu et al. (2018) Yu, P.-C., Yu, C.-H., Lee, C.-D., et al. 2018, AJ, 155, 91, doi: 10.3847/1538-3881/aaa45b
  * Yuan et al. (2020) Yuan, L., Li, G.-X., Zhu, M., et al. 2020, A&A, 637, A67, doi: 10.1051/0004-6361/201936625