11institutetext: Max-Planck-Institut für Radioastronomie, Auf dem Hügel 69,
53121 Bonn, Germany
11email<EMAIL_ADDRESS>22institutetext: Centre for Astrophysics
and Planetary Science, University of Kent, Canterbury, CT2 7NH, UK
33institutetext: Centre for Astrophysics Research, Science and Technology
Research Institute, University of Hertfordshire, College Lane, Hatfield AL10
9AB, UK

# High Resolution LAsMA 12CO and 13CO Observation of the G305 Giant Molecular
Cloud Complex : I. Feedback on the Molecular Gas.

P. Mazumdar High Resolution LAsMA 12CO and 13CO Observation of the G305 Giant
Molecular Cloud Complex : I. Feedback on the Molecular Gas.High Resolution
LAsMA 12CO and 13CO Observation of the G305 Giant Molecular Cloud Complex : I.
Feedback on the Molecular Gas. F. Wyrowski High Resolution LAsMA 12CO and 13CO
Observation of the G305 Giant Molecular Cloud Complex : I. Feedback on the
Molecular Gas.High Resolution LAsMA 12CO and 13CO Observation of the G305
Giant Molecular Cloud Complex : I. Feedback on the Molecular Gas. D. Colombo
High Resolution LAsMA 12CO and 13CO Observation of the G305 Giant Molecular
Cloud Complex : I. Feedback on the Molecular Gas.High Resolution LAsMA 12CO
and 13CO Observation of the G305 Giant Molecular Cloud Complex : I. Feedback
on the Molecular Gas. J. S. Urquhart High Resolution LAsMA 12CO and 13CO
Observation of the G305 Giant Molecular Cloud Complex : I. Feedback on the
Molecular Gas.High Resolution LAsMA 12CO and 13CO Observation of the G305
Giant Molecular Cloud Complex : I. Feedback on the Molecular Gas. M. A.
Thompson High Resolution LAsMA 12CO and 13CO Observation of the G305 Giant
Molecular Cloud Complex : I. Feedback on the Molecular Gas.High Resolution
LAsMA 12CO and 13CO Observation of the G305 Giant Molecular Cloud Complex : I.
Feedback on the Molecular Gas. K. M. Menten High Resolution LAsMA 12CO and
13CO Observation of the G305 Giant Molecular Cloud Complex : I. Feedback on
the Molecular Gas.High Resolution LAsMA 12CO and 13CO Observation of the G305
Giant Molecular Cloud Complex : I. Feedback on the Molecular Gas.

(Received 22.12.2020 / Accepted 21.05.2021)

###### Abstract

Context. Understanding the effect of feedback, the interaction of young
massive stars with their parental Giant Molecular Clouds, is of central
importance for studies of the interstellar medium and star formation.

Aims. We observed the G305 star forming complex in the $J=3\text{-}2$ lines of
^12CO and ^13CO to investigate how molecular gas surrounding the central
stellar clusters is being impacted by feedback.

Methods. The APEX telescope’s LAsMA multi-beam receiver was used to observe
the region. Excitation temperatures and column density maps were produced.
Combining our data with data from the SEDIGISM survey resulted in a ^13CO
$J=3\text{-}2/2\text{-}1$ excitation map. To verify whether feedback from
stellar clusters is responsible for exciting the gas, the distribution of CO
excitation was compared with that of 8$\,\mu\rm{m}$ emission imaged with
Spitzer, which is dominated by UV-excited emission from PAHs. Line centroid
velocities, as well as stacked line profiles were examined to investigate the
effect of feedback on the gas dynamics.

Results. Line profiles along radially outward directions demonstrate that the
excitation temperature and ^13CO $J=3\text{-}2/2\text{-}1$ ratio increase
steeply by factors of $\sim$ 2–3 at the edge of the denser gas traced by ^13CO
that faces the hot stars at the center of the complex and steadily decreases
away from it. Column density also increases at the leading edge, but does not
always decrease steadily outward. Regions with higher 8$\,\mu\rm{m}$ flux have
higher median excitation temperatures, column densities and ^13CO
$J=3\text{-}2/2\text{-}1$ ratio. The centroid velocity probability
distribution function of the region shows exponential wings, indicative of
turbulence driven by strong stellar winds. Stacked spectra in regions with
stronger feedback have higher skewness and narrower peaks with pronounced
wings compared to regions with weaker feedback.

Conclusions. Feedback from the stellar cluster in G305 has demonstrable
effects on the excitation as well as on the dynamics of the giant molecular
cloud.

###### Key Words.:

Submillimeter: ISM – ISM:clouds – ISM: kinematics and dynamics – ISM:
evolution – Line: profiles – Turbulence

##  1 Introduction

Massive stars ($M>8$\mathrm{M}_{\odot}$$) are rare and usually form inside
giant molecular clouds (GMCs) as the dominant members of young stellar
clusters (Motte et al., 2018). They are short lived ($\leq
30\,$\mathrm{M}\mathrm{y}\mathrm{r}$$), but are known to inject large amounts
of feedback into the interstellar medium in the form of stellar winds,
ionizing radiation and supernovae (Krumholz et al., 2014). These feedback
mechanisms can in turn trigger or disrupt the formation of the next generation
of stars when they interact with the natal molecular cloud. They can sweep up
the surrounding gas and create parsec-scale cavities around them (Deharveng et
al., 2010), forming dense shells of gas as a result and thereby triggering
star formation. Conversely, they can also completely disperse their
surrounding molecular gas suppressing star formation (Krumholz et al., 2014,
and references therein). The ability to both constructively and destructively
affect the formation of subsequent generation of stars means that high mass
stars play a significant role in driving the evolution of GMCs (Zinnecker &
Yorke, 2007). Here, we study the feedback of massive stars in the G305 HII
region and molecular cloud complex.

Figure 1: Three-color image (green = Spitzer-IRAC4 8 $\mu\rm{m}$, red =
Midcourse Space Experiment (MSX) 21.3 $\mu\rm{m}$, blue = Herschel-PACS 70
$\mu\rm{m}$) of the G305 star-forming complex. The 21.3 $\mu\rm{m}$ emission
is dominated by hot dust in the HII region. The colder gas is traced by the 70
$\mu\rm{m}$ emission. The interface between the ionized and molecular gas
appears as a blend of green (strong 8 $\mu\rm{m}$ emission from PAHs), blue
(colder molecular gas) and occasionally red (interfaces very close to HII
regions). The positions of Danks 1 and 2 clusters have been marked with the
smaller and the larger yellow circles respectively and the wolf-rayet star
WR48a has been marked as a filled white star.

### G305: a brief history

The Giant Molecular Cloud associated with G305 is one of the most massive and
luminous in the Milky Way (Fig. 1). It is located in the Galactic plane at
$l\sim$$\,,\,b\sim$$$ and at a kinematic distance of
$4\,$\mathrm{k}\mathrm{p}\mathrm{c}$$ (derived from a combination of radio and
H$\alpha$ observations by Clark & Porter (2004); Davies et al. (2012) measured
its spectrophotometric distance to be $3.8\pm
0.6\,$\mathrm{k}\mathrm{p}\mathrm{c}$$ and most recently Borissova et al.
(2019) measured the Gaia DR2 average distance to be $3.7\pm
1.2\,$\mathrm{k}\mathrm{p}\mathrm{c}$$), which places it in the Scutum-Crux
spiral arm. Given this distance, the complex has a diameter of $\sim
30\,$\mathrm{p}\mathrm{c}$$ (Clark & Porter, 2004) and a molecular mass of
$\sim 6\times 10^{5}\,\rm{M_{\odot}}$ (Hindson et al., 2010). The G305 complex
consists of a large central cavity that has been cleared by the winds from
massive stars belonging to two visible central clusters (Danks 1 and 2) and
the Wolf-Rayet star (WR48a) (Clark & Porter, 2004; Davies et al., 2012) and is
surrounded by a thick layer of molecular gas (traced by CO and NH3 emission;
Hindson et al., 2010, 2013). Radio continuum observations by Hindson et al.
(2012) have revealed that the cavity is filled with ionised gas and identified
6 ultra-compact HII (UC HII) regions and also one bright rimmed cloud (BRC) at
the periphery of the cavity, indicating molecular gas irradiated by UV
radiation (Sugitani & Ogura, 1994; Thompson et al., 2004), that may cause
implosion (Bertoldi, 1989) or evaporation. A number of studies have reported
star formation tracers (water and methanol masers, HII regions and massive
young stellar objects, MYSOs) (Clark & Porter, 2004; Lumsden et al., 2013;
Urquhart et al., 2014; Green et al., 2009, 2012). Furthermore, Hindson et al.
(2010) found the concentration of star formation tracers to be enhanced inside
a clump of NH3 bearing molecular gas that faces the ionising sources, which is
consistent with the hypothesis that the star formation has been triggered.
Analysis of the stellar clusters in the complex reveals them to have ages of
$1.5\,$\mathrm{M}\mathrm{y}\mathrm{r}$$ for Danks 1 and
$3\,$\mathrm{M}\mathrm{y}\mathrm{r}$$ for Danks 2, with the former possibly
being triggered by the latter (Davies et al., 2012). Additionally, a diffuse
population of evolved massive stars was also found to exist within the
confines of the G305 complex that had formed around the same time as the two
clusters (Leistra et al., 2005; Shara et al., 2009; Mauerhan et al., 2011;
Davies et al., 2012; Faimali et al., 2012; Borissova et al., 2019).

How feedback from the massive stars affects molecular clouds is still poorly
understood. However, the extensive amount of work done in identifying and
characterising the ongoing star formation taking place in this complex (UC
HIIs, deeply embedded protostars and protoclusters) and mapping the
distribution of molecular and ionized gas, makes G305 the ideal laboratory to
study the role of feedback in affecting molecular cloud structures and
creating future generation of stars. We have divided our work into two
separate parts. In this paper, we want to further our understanding of how
feedback from the central population of stars and the UC H II regions in G305
have affected the molecular gas. In the second paper of this series we will
decompose the GMC into clumps and investigate whether any discernible
differences exist in properties of clumps experiencing feedback compared to
those further away from the feedback region.

So far, the evidence of feedback on the molecular gas in G305 has mostly been
phenomenological and qualitative. In this paper, we study the excitation and
kinematics of the gas in the complex since that is the most direct evidence of
the feedback affecting the molecular cloud. Hindson et al. (2013) observed the
$J=1\text{-}0$ line of the CO main isotopologue to trace the distribution of
molecular gas with a resolution of $>30$\mathrm{\SIUnitSymbolArcsecond}$$.
Since, the compressed layer of gas due to the feedback is expected to be thin,
resolving it requires a higher angular resolution. The feedback region will
also exhibit higher excitation of gas that needs to be verified with
excitation studies. In addition, the ^12CO becomes optically thick for
moderately dense clouds ($\sim 10^{3}\,${\mathrm{cm}}^{-3}$$ at
$25\,$\mathrm{K}$$ for the ($J=1\text{--}0$) transition) and consequently,
provides unreliable measurements. This necessitates the need for observations
with rarer isotopologues of CO. Finally, observations of the dispersed gas
requires sensitivity to very low column densities. Therefore, we decided to
use the Large APEX sub-Millimeter Array (LAsMA) seven pixel array on the
Atacama Pathfinder EXperiment (APEX) 12 meter sub-millimeter telescope to
observe the G305 complex in the $J=3\text{-}2$ rotational transition of both
^12CO and its ^13CO isotopologue.

The paper is organized as follows. We describe the observation methods and
data reduction techniques in Sect. 2. We then present the results and the
following analyses of the data along with their discussions in Sects. 3 \- 7.
In Sect. 8 we summarize the findings of this paper.

##  2 Observation and Data Reduction

###  2.1 Observations

We mapped a $1\degree\times 1\degree$ area centred on $(l,b)=(305.0,0.0)$. The
observations were done between 2017 and 2019 using the APEX telescope (Güsten
et al., 2006) under the project number M-099.F-9527A-2017. The APEX telescope
is located at an altitude of $5100\,$\mathrm{m}$$ at Llano de Chajnantor, in
Chile.111This publication is based on data acquired with the Atacama
Pathfinder EXperiment (APEX). APEX is a collaboration between the Max-Planck-
Institut für Radioastronomie, the European Southern Observatory and the Onsala
Space Observatory.

The receiver employed for these observations was the 7 pixel LAsMA MPIfR PI
instrument operating in the frequency range of
$270-$370\text{\,}\mathrm{GHz}$$ (Güsten et al., 2008). It is a hexagonal
array of six pixels surrounding a central pixel. The outer array is separated
from the central pixel by $\sim 2$ FWHM. The pixels employ superconductor-
insulator-superconductor (SIS) sideband separating mixers (2SB). The backend
consisted of Fast Fourier Transform Spectrometers (FFTS4G) that cover an
intermediate frequency (IF) bandwidth of 4–8 $\mathrm{GHz}$ instantaneously
with 65536 spectral channels with a width of $61.03\text{\,}\mathrm{kHz}$.

In order to observe both $\ce{{}^{13}CO}$ ($\nu_{\text{rest}}\sim
330.588\,$\mathrm{GHz}$$) and $\ce{{}^{12}CO\,(3-2)}$ ($\nu_{\text{rest}}\sim
345.796\,$\mathrm{GHz}$$) simultaneously the local oscillator frequency was
set at $338.190\text{\,}\mathrm{GHz}$. This frequency was chosen in order to
avoid contamination of the $\ce{{}^{13}CO}\,(3\text{-}2)$ lines due to bright
$\ce{{}^{12}CO}\,(3\text{-}2)$ emission from the image band. For this setup,
the FWHM is $\sim$19\text{\,}\mathrm{\SIUnitSymbolArcsecond}$$, and the
velocity resolution is $0.053\text{\,}\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$.
The whole 1 square degree region was divided into four sub-maps – one for each
quadrant centered around $l=$$\,,\,b=$$$. Each sub-map was further divided
into 9 smaller sub-maps of size
$$10\text{\,}\mathrm{\SIUnitSymbolArcminute}$\times$10\text{\,}\mathrm{\SIUnitSymbolArcminute}$$
each. Observations were performed in a position switching on-the-fly (OTF)
mode. The reference-positions were carefully chosen and tested to ensure no
emission was present in the velocity range of
$-150\,\text{to}\,$50\text{\,}\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$$ (see
Sect. A for details about the reference positions). For each scan, the 7
pixel-array was rotated to an angle of $None$ in equatorial coordinates to
ensure minimal overlap between the pixels and maximize sky coverage. For each
OTF scan, data were dumped every $7\text{\,}\mathrm{\SIUnitSymbolArcsecond}$
scanned. On reaching the edge of every mapped area, the array was shifted
perpendicular to the scan direction by half the beam-width
($9\text{\,}\mathrm{\SIUnitSymbolArcsecond}$) and the scan was then carried
out in the reverse direction. This process was repeated until the whole sub-
map was observed. The same sub-map was then observed in a $None$ rotated frame
to ensure Nyquist sampling was achieved along both directions and also to
reduce systematic scanning effects. During each scan, a calibration
measurement was made every 10-15 minutes. This setup of a sample spacing of
$\sim$7\text{\,}\mathrm{\SIUnitSymbolArcsecond}$$ along with a sampling time
of $0.1\text{\,}\sec$ resulted in datacubes of size
$10$\mathrm{\SIUnitSymbolArcminute}$\,\times\,10$\mathrm{\SIUnitSymbolArcminute}$$
in approximately 1 hour.

The calibration of the spectral lines was carried out using the
apexOfflineCalibrator pipeline (Muders et al., 2006; Polehampton et al.,
2019). It uses a three load chopper wheel method, which is an extension of the
“standard” method used for millimetre observations (Ulich & Haas, 1976) to
calibrate the antenna temperature scale. To remove the spectral variations of
the atmosphere across the bandpass, the ATM model (Pardo et al., 2001) was
used. The pipeline provides the flexibility to determine the opacity for the
whole band pass as one number or to calculate a more accurate opacity channel
by channel. We chose the latter for calibrating our data since the ^13CO line
lies at the edge of an atmospheric water line at 325 GHz and hence an accurate
accounting for this line in the bandpass is essential. After the calibration,
the intensities are obtained on the $T^{*}_{A}$ (corrected antenna
temperature) scale. Apart from the atmospheric attenuation, this also corrects
for rear spillover, blockage, scattering and ohmic losses. All intensities
stated in this paper are in the $T^{*}_{A}$ scale, unless specifically stated
otherwise. Regular observations of Jupiter were done during the commissioning
of the instrument and the observations of G305, resulting in a beam efficiency
of $\eta_{mb}=0.74$ with an uncertainty of about $10\%$. This efficiency value
was used to convert intensities from $T^{*}_{A}$ scale to the main beam
brightness temperature ($T_{mb}$).

###  2.2 Data Reduction

The data was reduced using the GILDAS
package222http://www.iram.fr/IRAMFR/GILDAS. A velocity range of
$-200\text{\,}\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$ to
$200\text{\,}\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$ was extracted from every
spectrum and resampled to an adequate velocity resolution of
$0.5\text{\,}\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$ to reduce the noise. The
velocity range $-150\text{\,}\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$ to
$50\text{\,}\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$ was masked before fitting a
3rd order baseline to each spectrum. The reduced, calibrated data obtained
from the different scans were then combined and gridded using a
$6$\mathrm{\SIUnitSymbolArcsecond}$$ cell size. The gridding process includes
a convolution with a Gaussian kernel with a FWHM size of one-third the
telescope FWHM beam width. The data cubes obtained have a final angular
resolution of $\sim 20$\mathrm{\SIUnitSymbolArcsecond}$$. Spectra from all the
pixels were then averaged to find the portions of the spectra containing line
emission, which were then masked. The process of baseline removal was again
repeated for the spectra of each pixel to obtain a more stable baseline and a
cleaner map.

Figure 2: Moment-0 maps of ^12CO (3-2) [left] and 13CO (3-2) [right] lines
towards the G305 GMC complex. In both maps, the emission has been integrated
over a velocity range from $-70$ to
$+10\,$\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$$. Pixels with no emission
$>5\sigma$ for at least three consecutive velocity channels have been excluded
(seen in white). Overlaid on top as green stars are the position of stars as
reported in Borissova et al. (2019). The red circles show the positions of the
Danks 1 and 2 clusters and the red star is WR48a. The numbered regions are
discussed in the text.

##  3 Integrated Properties

###  3.1 Moment-0 Maps

In order to create the integrated intensity (“moment-0”) maps of the G305
region, a noise map of each grid-element (referred to as pixel from now
onwards) was first created for both the ^12CO and ^13CO $J=$ 3-2 transitions.
This was done by calculating the standard deviation for a part of the spectrum
consisting of 100 emission free channels. Fig. 17 shows the pixel-wise noise
of the whole region in both ^12CO and ^13CO $J=$ 3-2 data sets. The moment-0
map was produced by integrating the emission above 5$\sigma$ between
$-70\text{\,}\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$ and
$10\text{\,}\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$. Fig. 2 shows our moment-0
maps of the G305 star forming complex. The ^12CO map traces the large scale,
diffuse as well as hot gas very well.

The ^13CO map on the other hand is sensitive to higher column density gas and
hence, traces the more compact, dense clumps in the complex333Due to the high
opacity of ^12CO and a resulting much lower effective critical density, the
^13CO transition probes significantly higher H2 volume densities in the
clouds. We have divided the map into nine regions for ease of explanation.
This demarcation of the regions was done visually to highlight relevant
molecular gas features observed in the channel-maps. From the two integrated
maps it can be seen that the central region of the giant molecular cloud has
been cleared out of most of the high density gas. Although it is reasonable to
believe that the central stars clusters are responsible for this, it still
needs to be verified whether the amount of feedback from the stars in the
complex can indeed carve out such a large hole. This will be explored in
Sect.5.

Looking at the gas content of the complex, we observe three bright dense
molecular cloud complexes. One in the (Galactic) north (region V and VI in
Fig.2), one in the south (region VIII) and the third in the east (region III)
of the central cavity. The northern and the southern complex are connected by
a thin strip of high(er) column density tenuous gas (region VII) towards the
west. Both of these complexes also show a carved-out hole in their center
where one O and two B stars have been observed (Leistra et al., 2005;
Borissova et al., 2019). The cloud to the east (III) is disconnected from the
others but has a long very straight ($\sim 20\,\times\,2\,$pc) filamentary
structure (III and I) trailing away from the cavity itself. It has a central
velocity of $\sim 40\,$\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$$ and a gradient
of $\sim 0.25\,$\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$\text{pc}^{-1}$. Such
filaments are found to be associated with many star-forming regions and are
believed to play a crucial role in star-formation (André, 2017). The north-
east of the cavity appears as a wind-blown structure delineated by regions II,
III, IV and V. Towards the south of the cavity (between regions III and VIII),
the gas also appears to have been dispersed by the feedback.

###  3.2 Velocity structure

Fig. 3 shows the average spectrum over the whole region. There is no confusion
in the foreground except for some local emission at
$\sim-4\,$\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$$ in ^12CO. The line profile
is not Gaussian. All emission from the complex is found within the velocity
range between $-50$ and $-26\,$\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$$ for
^13CO and $-55$ and $-7\,$\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$$ for ^12CO.

Figure 3: Averaged spectrum of ^12CO and ^13CO over the whole G305 giant
molecular cloud complex. The ^13CO line has been scaled up by a factor of 3.
Figure 4: Channel maps of ^12CO(3-2) emission towards G305. The emission has
been integrated over $5\,$\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$$ around the
velocities indicated in each panel.

Fig. 4 shows the channel maps of G305 for the range of velocities $-50\rm{\
to}-25\,$\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$$ with a spacing of
$5\,$\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$$. Regions I and VIII are prominent
in the range $-25$ to $-35\,$\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$$, while
the other regions (II, III, IV, V, VI and VII) emit in the range $-35$ to
$-45\,$\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$$. The observed velocity
structure is most likely a consequence of the interplay of the morphology of
the cloud and the feedback from the central star clusters on the natal
molecular cloud. For a comprehensive analysis of the morphology of the cloud
we refer to Hindson et al. (2013) who studied the region reported here in more
detail by comparing the molecular emission with the morphology of the surfaces
of molecular clouds illuminated by the far-ultraviolet (FUV) photons of the
stellar sources, commonly refered to as photon dominated regions (PDR)
(Tielens & Hollenbach, 1985). Our results are consistent with the picture
presented by these authors.

##  4 LTE Analysis

The CO data were combined to calculate the excitation temperature, optical
depth, and column density. We assume that the molecular gas can be described
as a system in Local Thermodymanic Equilibrium (LTE) and the brightness
temperature ($T_{B}$) is equal to the measured $T_{mb}$. Then, solving the
radiative transfer equation for an isothermal slab of CO radiating at a
frequency $\nu$ we obtain:

$\frac{T_{B}}{$\mathrm{K}$}=[J_{\nu}(T_{ex})-J_{\nu}(T_{bg})]\cdot\left(1-e^{-\tau_{\nu}}\right)$
(1)

where $T_{ex}$ is the excitation temperature of the line; $T_{bg}$ is the
temperature of the cosmic microwave background; $\tau_{\nu}$ is the optical
depth; and, $J_{\nu}(T)$ is the equivalent temperature of a black body at
temperature $T$ which can be written as:

$\frac{J_{\nu}(T)}{$\mathrm{K}$}=\frac{h\nu}{k_{B}}\left(\frac{1}{e^{h\nu/k_{B}T}-1}\right)$
(2)

$h$ is the Planck’s constant and $k_{B}$ is the Boltzmann constant.

All the calculations were done on each $l,b,v$ three-dimensional pixel (from
here on referred to as voxel). The advantage of this methodology over that of
deriving properties over the velocity integrated values is that all the
subsequent properties derived are independent of any segmentation method used
for source extraction.

To calculate the 12CO excitation temperature, we adopt the textbook formalism
(Wilson et al., 2013), which assumes that the 12CO (3-2) line is optically
thick. This was then used to determine the 13CO optical depth and subsequently
the 13CO column density. Eq. 1 is used to calculate the excitation
temperature. Using a value of $2.7\,$\mathrm{K}$$ for the (cosmic microwave
radiation) background temperature, we obtain:

$\frac{T_{ex}}{$\mathrm{K}$}=16.6\,\left[\ln{\left(1+\frac{16.6}{T_{12}+0.04}\right)}\right]^{-1},$
(3)

where we use $T_{12}$ and $T_{13}$ for the main-beam brightness temperature of
12CO and 13CO, respectively. All the voxels satisfied the condition
$T_{12}>T_{13}$; so, we did not have any significant case of self-absorption
in our data that would have rendered the excitation temperature derived from
this method unreliable.

The optical depth is derived for each voxel from the excitation temperature
obtained from 12CO and the 13CO intensity using the following equation derived
from Eq. 1:

$\tau_{13}=-\ln\left[1-\frac{T_{13}}{15.9}\left(\frac{1}{e^{15.9/T_{ex}}-1}-0.0028\right)^{-1}\right],$
(4)

where $\tau_{13}$ denotes the optical depth of 13CO $(3\text{-}2)$ transition.
Only those voxels that have an emission greater than 5$\sigma$ are considered
real.

The column density of 13CO $J=2$ level is calculated as:

$\frac{N_{13}(J=2)}{${\mathrm{cm}}^{-2}$}=\frac{8\pi}{c^{3}}\frac{g_{2}}{g_{3}}\frac{\nu^{3}}{A_{32}}\frac{1}{1-e^{(-h\nu/k_{B}T_{ex})}}\,\tau_{\nu}\,dv,$
(5)

where $g_{2}$ and $g_{3}$ are statistical weights of $J=2$ and $J=3$
rotational energy levels respectively; $A_{32}=2.181\times
10^{-6}\,${\mathrm{s}}^{-1}$$ is the Einstein’s A coefficient for the 13CO
$(3\text{-}2)$ transition (taken from the Leiden Atomic and Molecular
Database444https://home.strw.leidenuniv.nl/~moldata/CO.html; Schöier et al.,
2005).

The rotational partition function, $Z$, can be approximated by

$Z\approx\frac{k_{B}}{hB}\left(T_{ex}+\frac{hB}{3k_{B}}\right),$ (6)

where $B=h/(8\pi^{2}\mathcal{I})$ is the rotation constant and is calculated
using the moment of inertia $\mathcal{I}=\mu R_{CO}^{2}$, and $\mu$ is the
reduced mass, and $R_{CO}=0.112\,$\mathrm{nm}$$ is the mean atomic separation
of the CO molecule.

Finally, using $N_{13}(J)$ and $Z$ one can calculate the total column density
of 13CO using:

$\frac{N_{13}}{${\mathrm{cm}}^{-2}$}=N_{13}(J)\frac{Z}{2J+1}\exp{\left[\frac{hBJ(J+1)}{k_{B}T_{ex}}\right]}$
(7)

### Sub-Thermal Excitation

The analysis presented in this section is based on the assumption that LTE is
applicable in all the voxels with detected emission. But for gas with
densities below the critical density of CO (3-2) ($\approx
10^{4}\,${\mathrm{cm}}^{-3}$$), the energy level populations will not follow
the Boltzmann distribution and consequently the measured excitation
temperature will be lower than the actual temperature of the gas. An
underestimation of the excitation temperature will lead to an overestimation
of the column density values according to Eq.5. But, for optically thick
emission the critical denisity can be effectively reduced (roughly by
$1/\tau$) thereby making it possible for the gas to reach LTE at lower
densities. We tried to test whether the limit of large optical depth for ^12CO
holds in regions where ^13CO is also detected. For this, we took the lowest
detected ^13CO column density at a $5\sigma$ significance and estimated the
^12CO column density adopting a ^12CO/^13CO abundance ratio of 60.

Figure 5: Left: Mean $T_{ex}$ map of the G305 complex. For each pixel this was
calculated by integrating over all the channels. Only those channels that had
emission above 5$\sigma$ noise level were considered. Right Integrated 13CO
Column Density map of G305. This was calculated by summing the 13CO total
column density per channel over all the channels. Overlaid on top, are the
positions of the HII regions (triangles), UC HII regions (diamonds) and the
BRC (star) as determined by Hindson et al. (2012, 2013).

This value was calculated using the equation $12C/13C=6.21D_{GC}+18.71$ from
Milam et al. (2005) where $D_{GC}\approx
6.6\,$\mathrm{k}\mathrm{p}\mathrm{c}$$ is the galactocentric distance of G305.
The estimated ^12CO column density corresponding to the lowest detected ^13CO
column density is then $\sim\,2.46\times 10^{17}\,${\mathrm{cm}}^{-2}$$. Eq.5
was then used to calculate the velocity integrated optical depth for
^12CO(3-2) transition. We obtained $\int\tau_{\nu}dv\approx
149.193\,$\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$$ for an excitation
temperature of $15\,$\mathrm{K}$$. Assuming a Gaussian line profile with a
standard deviation of $\sim 8.5\,$\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$$ (see
Sect.7.2 for the justification of the chosen value for standard deviation),
the optical depth at the centroid velocity is given by
$\tau_{12}=\left(\int\tau_{\nu}dv\right)/\left(\sigma_{v}\cdot\sqrt{2\pi}\right)\approx
7$. So, for pixels with detected ^13CO emission, the ^12CO optical depth is
greater than 1. This along with the findings of Hindson et al. (2010) that the
volume density of clumps in G305 ranges between
$10^{3}\text{--}10^{4}\,${\mathrm{cm}}^{-3}$$ means that the emission from the
pixels where both ^12CO and ^13CO are detected are most likely in LTE. In the
other regions where only ^12CO emission is detected, the condition of LTE may
not always apply and should be kept in mind while interpreting the results
derived from them.

##  5 Effects of Feedback on the Molecular Gas

###  5.1 Excitation Temperature and Column Density maps

The integrated spectrum over the whole G305 region (see Fig. 3) does not show
any obvious sign of confusion along the line of sight (the emission appears to
come from one local standard of rest (LSR) velocity without foreground
confusion at any other velocity channel). Hence, properties like excitation
temperature and column densities integrated over the whole linewidth are very
likely to be a good representation of the corresponding physical properties of
the GMC.

Fig. 5 (left) shows the excitation temperature map of the complex where each
pixel represents the mean 12CO excitation temperature at the corresponding
position. Fig. 5 (right) shows the 13CO column density of the region summed
over all velocity channels on a logarithmic scale. The hot regions towards the
northern, southern and western molecular clouds are coincident with the HII
and UC HII regions existing in the region (see Fig. 5; Hindson et al., 2012,
2013). The UC HII regions are also located in regions of high column density
surrounded by a region with relatively lower column density. One also notes
some unconnected small regions where the column density seems to be much
higher than in some of the densest regions inside the larger molecular clouds,
notably at approximately $(l,b)\sim(305\degree 42\arcmin,+0\degree
19\arcmin),(305\degree 30\arcmin,+0\degree 13\arcmin)$ and $(305\degree
10\arcmin,-0\degree 8\arcmin)$. Of these, only that at $\sim(305\degree
30\arcmin,+0\degree 13\arcmin)$ is associated with a diffuse H II region
G305.4399+00.2103. For other sources we have not found any counterparts in the
literature.

In Fig.5 we notice that the edge of the denser clouds show a marked jump in
their excitation temperature at the side facing the central stellar clusters,
which then tapers off as we move away from the center. This represents clear
evidence that feedback from the stars acting on the edge of the dense gas is
heating it. The exposed gas then acts as a shield for the rest of the cloud,
resulting in a temperature profile that decreases as we move away from the
center. Fig. 6 shows the profiles of ^13CO column density (top panel row) and
excitation temperature (second row of panels from the top) along two different
arbitrarily selected directions leading away from the center as marked on Fig.
5. These profiles have been obtained after smoothing the excitation
temperature and column density maps to a resolution of
30$\mathrm{\SIUnitSymbolArcsecond}$ in order to compare them with other
ancillary data as will be evident in the following sections. The left panel
shows the profile along the line marked N and the right panel shows that along
S. As is evident from the excitation temperature profiles, the gas is heated
on the leading edge of the molecular cloud facing the central cavity. The
feedback from the stars results in a steep increase in the temperature by a
factor of $\sim 3$ at the edge facing the center. The temperature then
steadily drops as we move away from the center. As pointed out in Sect.4 the
excitation temperature before the leading edge of the profile may have been
underestimated. So the increase in its value at the leading edge can be
considered to be an upper limit. For the column density profiles, we notice
that the northern profile also shows a pronounced evidence for compression as
the column density at the leading edge is enhanced significantly compared to
the trailing edge. However, for the southern profile even if the leading edge
of the cloud has a higher column density than the rest of the cloud, the
decrease in column density as we move away from the center is not as
pronounced. Due to the absence of significant ^13CO emission between the stars
and the dense gas boundary, we were only able to determine a lower limit on
the extent of the region that has an increased column density at the edge of
the cloud (based on the minimum column density
($\approx$4.1\text{\times}{10}^{15}$\,${\mathrm{cm}}^{-2}$$ corresponding to
$5\sigma$ times the rms noise value probed by our observations). This lower
limit factor of $\gtrsim 5$ for S and $\gtrsim 10$ for N still represents a
large increase in column density at the edge of the cloud.

Figure 6: 13CO Column Density (grey), Excitation Temperature (orange), ^13CO
$J=3\text{-}2$/$J=2\text{-}1$ ratio (green), and 8$\mu m$ Flux (purple)
profiles for two separate directions in G305. The profiles were plotted
outwards from the center of the complex.

###  5.2 Rotational excitation

The energy from the feedback being deposited onto the molecular cloud from the
stars may be used up to excite the CO molecules to their higher $J$ rotational
levels. In this section, we investigate whether feedback in G305 affects the
rotational excitation in the molecular cloud. We complemented our data with
13CO $J=2\text{-}1$ data from the SEDIGISM (Schuller et al., 2017) survey to
create rotational excitation maps for the region.

For this, the LAsMA 13CO $J=3\text{-}2$ map was first smoothed to the
$30\arcsec$ angular resolution of the SEDIGISM map. In order to trace the
excitation, the 13CO $J=3\text{-}2$/$J=2\text{-}1$ intensity ratio was
calculated over the whole map. Pixels with a signal-to-noise ratio (S/N from
now on) of less than 5 were blanked. Warm and dense gas is excited to higher
$J$ levels resulting in a higher 13CO ($J=3\text{-}2$)/($J=2\text{-}1$) ratio.

Figure 7: ^13CO $J=3\text{-}2$/$J=2\text{-}1$ ratio map of the G305 complex.
The dashed lines show the direction along which the profiles of the excitation
ratio was plotted in Fig. 6. The black circles show the locations of the Danks
1 and 2 clusters. The black star shows the position of WR48a, and the red
stars show the positions of the stars from Borissova et al. (2019).

Fig. 7 shows the map of the ratio of the two line intensities. It is evident
that this ratio is higher on the side of the cloud facing the central cavity.
We also show two directional profiles cut through the excitation map in Fig.6
(third row of panels from the top). Both these profiles demonstrate the effect
of feedback very well. In a very narrow region facing the center we see the
excitation ratio almost equal to 1. For linear molecules, the rotational
excitation can either increase by higher temperatures or larger volume
densities or a combination of both, indicating a higher pressure at the cloud
surfaces. As we then move away from the center, the excitation ratio decreases
fast, indicating that the front end of the cloud is acting as a shield for the
rest of the gas trailing it.

###  5.3 Energetics of Feedback

In this subsection, we try to explore whether the energy input from the
central stars can account for the observed effects on the molecular gas
morphology and excitation. Firstly, the OB stars inside the cavity of G305 can
efficiently ionize the surrounding gas with the large amounts of ionizing
photons they emit leading to photoevaporation of the cloud. Here, we estimate
if this can lead to the observed size of the cavity given the age and type of
stars in the complex. We follow the model used by Watkins et al. (2019) for a
simple case of a spherical cloud of uniform density $n_{H}$ being illuminated
by a central stellar population emitting photons isotropically at rate
$\mathcal{N}_{i}$. The radius of the central hole carved out by these photons
in time $t$ given an electron density $n_{e}$ is given by the following
equation.

$R_{ion}=\left(\frac{3\mathcal{N}_{i}}{4\pi\alpha_{B}n_{e}^{2}}[1-\text{exp}(-n_{e}^{2}\alpha_{B}t/n_{H})]\right)^{\frac{1}{3}},$
(8)

where $\alpha_{B}$ is the recombination coefficient. Considering the stars
from the Danks1 and Danks2 as well as those outside the two clusters as
reported in Borissova et al. (2019) as the ionizing sources, we obtain
$\mathcal{N}_{i}\approx 9.4\times 10^{50}\,${\mathrm{s}}^{-1}$$ using the
stellar classification from Davies et al. (2012); Borissova et al. (2019) and
calculating the ionizing flux for different stellar types using Panagia (1973)
and Crowther (2007). We adopt $n_{H}\approx 10^{4}\,${\mathrm{cm}}^{-3}$$ and
$\alpha_{B}=2.7\times 10^{-13}\,${\mathrm{cm}}^{3}\text{\,}{\mathrm{s}}^{-1}$$
(Hindson et al., 2010, 2013), $n_{e}=[100-5000]\,${\mathrm{cm}}^{-3}$$. Figure
8 shows the diameter of the ionized bubble as a function of time for a range
of $n_{e}$ values. Given the diameter of the central cavity is
$\sim\,10\,\text{pc}$ wide along the north-south direction (between regions V
and VIII) and $\sim\,30\,\text{pc}$ across the east-west direction (between
regions III and VII), this would imply that the population of visible stars
inside the complex can drive such a cavity via photoionization given an
$n_{e}\sim\,10^{2}\,${\mathrm{cm}}^{-3}$$. But, this is a very simplistic
view, as the starts in the cavity are not located at its center but are spread
out over $\sim 20\,$\mathrm{p}\mathrm{c}$$. Also, electron density inside HII
regions is not constant over time and varies from
$10^{2}\text{--}10^{5}\,${\mathrm{cm}}^{-3}$$ depending on the diameter of the
cavity as $n_{e}\propto D^{-1}$ (Kim & Koo, 2001; Garay & Lizano, 1999). A
more realistic scenario would be one where the expansion of the cavity is
initially driven by the Danks 2 system for the first
$1.5\,$\mathrm{M}\mathrm{y}\mathrm{r}$$ which swepng out some of the ionized
gas via strong winds (aided by the WR stars outside the Danks cluster) and
thereby lowering the $n_{e}$ for the next generation of stars in Danks 1 and
the others. The subsequent generations of stars could then clear out the gas
more effectively.

Figure 8: Time evolution of the ionization diameter of a spherical cloud of
density $10^{4}\,${\mathrm{cm}}^{-3}$$ being illuminated by Danks1 and Danks2
star clusters at its center for different electron density values. The
vertical dotted line is the minimum age of the Danks1 cluster take from Davies
et al. (2012).

Next, we estimate whether the amount of energy input from the stars is large
enough to cause the observed trend in the excitation line profiles, even if
the nature of the profiles strongly suggest that feedback from the stars is
heating the gas. For this we first calculate the external pressure exterted by
the stars on the cloud surface. Assuming that most of the energy input from
stellar radiation comes from the ionizing photons, the pressure from stars can
be estimated as $P_{\rm{star}}=\mathcal{N}_{i}\,\langle
h\nu\rangle/4\pi{R_{s}}^{2}\,c\,k$, where $\langle h\nu\rangle$ is the mean
photon energy of an O-star (assumed to be $\sim 15\,\rm{eV}$ (Pellegrini et
al., 2007)), $R_{s}$ is the distance of the cloud from the emitting star, $c$
is the speed of light and $k$ is the Boltzmann’s constant. We assume that the
O5-O6V, B0-B1V and B2-B3V stars found by Leistra et al. (2005) in the
G305.3+0.2 cluster are the stars responsible for the observed excitation
profile N and Danks1 is responsible for that in S. But the spectral
classification of stars in Danks1 by Davies et al. (2012) spans a large range
of ionising flux values. In order to obtain a lower limit on the ionising
flux, we used the spectral type with the lowest ionising flux, i.e. O6V for
O4-6, O8V for O6-8/8If, B3V for O8-B3, B3I for O8-B3I and WN9 for WNLh. We
estimate a distance of 2.5 pc between the edge of the profile N and the stars
and $\sim 4$ pc between Danks1 and the edge of S. Using these values we obtain
the external pressure from the stars for N and S to be $P_{\rm{star,N}}\sim
2.5\times 10^{5}\,$\mathrm{K}\text{\,}{\mathrm{cm}}^{-3}$$, and
$P_{\rm{star,S}}\sim 2.6\times
10^{5}\,$\mathrm{K}\text{\,}{\mathrm{cm}}^{-3}$$ respectively. We then
calculate the thermal pressure at the edge of the cloud facing the cavity and
that at the far end away from the cavity. The pressure exerted by thermal
motion inside a cloud can be estimated as
$P_{th}=n(H_{2})\,T\,$\mathrm{K}\text{\,}{\mathrm{cm}}^{-3}$$. For the far end
of the cloud in both cases N and S, we assume the density to be equal to the
average value of clump densities from Table 5 in Hindson et al. (2013), i.e.
$n(H_{2})\sim 1.5\times 10^{3}\,${\mathrm{cm}}^{-3}$$. For the temperature we
adopt a value of $T\sim 10\,$\mathrm{K}$$ for both N and S (see Fig.6). So,
for both N and S the thermal pressure in the far end of the cloud is
$P^{far}_{th}=1.5\times 10^{4}\,$\mathrm{K}\text{\,}{\mathrm{cm}}^{-3}$$. For
the side of the profiles N and S facing the cavity, we need to deduce the
value of $n_{H_{2}}$. For this we assume that the pressure from the stars only
compresses the cloud in a direction along the plane of the sky. We can then
equate the proportional increase in column density to that of the observed
volume density. From Fig.6 we calculate the proportional increase in column
density at the edge facing the center compared to that away from the cavity to
be $\sim 4$ for N and $\sim 1.6$ for S. Now calculating the thermal pressure
at the edge of the profiles facing the central cavity we obtain
$P^{near}_{th,N}=28\cdot 4\cdot 1.5\times 10^{3}=1.68\times
10^{5}\,$\mathrm{K}\text{\,}{\mathrm{cm}}^{-3}$$ and $P^{near}_{th,S}=22\cdot
1.6\cdot 1.5\times 10^{3}=5.28\times
10^{4}\,$\mathrm{K}\text{\,}{\mathrm{cm}}^{-3}$$. The difference in the
thermal pressure between the leading and trailing edge for N and S is
therefore $\Delta P_{th,N}\sim 1.53\times
10^{5}\,$\mathrm{K}\text{\,}{\mathrm{cm}}^{-3}$$ and $\Delta P_{th,S}\sim
3.78\times 10^{4}\,$\mathrm{K}\text{\,}{\mathrm{cm}}^{-3}$$ respectively. This
difference in thermal pressure accounts for $\sim 61\%$ of $P_{\rm{star,N}}$
and less than $\sim 14.5\%$ of $P_{\rm{star,S}}$. Hence, for the profile N
about $61\%$ of the radiation pressure is going towards heating up the gas
whereas for S this is less than $15\%$.

##  6 Characterizing Feedback in G305

So far, the evidence of feedback on the molecular gas in G305 has been mostly
based on morphology, with specific examples of profiles along selected
directions. In this section we attempt to quantitatively study the effect of
feedback on the excitation of the gas at a global level over the whole cloud
complex. In order to see this global nature of the gas excitation in feedback
regions, we first need to identify as well as quantify where these feedback
regions are.

###  6.1 Identifying feedback regions : GLIMPSE 8$\mu\rm{m}$ map

The 8 $\mathrm{\SIUnitSymbolMicro m}$ map obtained from the Galactic Legacy
Infrared Mid-Plane Survey Extraordinaire (GLIMPSE: Benjamin et al., 2003;
Churchwell et al., 2009) is a very useful tool to identify the regions of
stellar feedback.

Figure 9: GLIMPSE $8\,$\mathrm{\SIUnitSymbolMicro m}$$ map of the G305
regions. The black contours correspond to the 12CO J=3–2 integrated
intensities of 30, 70 and 120
$\mathrm{K}\text{\,}\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$ (50, 120 and
200$\sigma$, respectively). The dashed lines show the direction along which
the profiles of the excitation ratio was plotted in Fig. 6.

PDRs mark the boundary between the ionized and neutral gas in a molecular
cloud (Rathborne et al., 2002). The FUV photons from stars excite polycyclic
aromatic hydrocarbons (PAHs) on the surface of dense molecular clouds at the
interface between the ionization front and the molecular gas (Tielens, 2008).
The PAHs absorb FUV radiation from hot stars and re-emit fluorescently in
several broad bands at near and mid infrared (IR) wavelengths (Allamandola et
al., 1989). The most luminous of these is within the $6.5\text{ to
}9\,$\mathrm{\SIUnitSymbolMicro m}$$ range covered by the 8$\,\mu$\mathrm{m}$$
filter of the Infrared Array Camera (IRAC: Fazio et al., 2004) aboard the
Spitzer Space Observatory that was employed for GLIMPSE. Hence, bright regions
in 8 $\mathrm{\SIUnitSymbolMicro m}$ Spitzer/IRAC images correspond to regions
subjected to large amounts of radiative feedback to FUV radiation from the
stars.

Fig. 9 shows the Spitzer 8$\,\mu$\mathrm{m}$$ image of the G305 region. The
molecular gas in the region seems to be coextensive with the bright
8$\,\mu$\mathrm{m}$$ emission. All of the CO emission in the region is
associated with IR emission. In order to demonstrate the validity of the
8$\,\mu$\mathrm{m}$$ flux as a tracer for feedback we plotted its profiles
along the same direction as the excitation temperature, column density and the
13CO $J=3\text{-}2$/$J=2\text{-}1$ intensity ratio in Fig. 6. Before plotting
the profile, the 8 $\mathrm{\SIUnitSymbolMicro m}$ map was first smoothed to
the same resolution as the other excitation maps of
30$\mathrm{\SIUnitSymbolArcsecond}$. At the edges of the higher column density
clouds, we observe a sharp increase in the 8$\,\mu$\mathrm{m}$$ flux (around a
depth of $7\,$\mathrm{p}\mathrm{c}$$ for N and $1.5\,$\mathrm{p}\mathrm{c}$$
for S), marking the brightest parts of the PDRs of the clouds. This increase
coincides with the increase in the gas excitation properties. Afterwards, all
three properties decrease along with the 8$\,\mu$\mathrm{m}$$ flux. The
decreasing profile as we move away from the center also demonstrates that the
PDR is effectively shielding the molecular cloud, absorbing the bulk of the
FUV photons. Inside the denser cloud along N, the 8$\,\mu$\mathrm{m}$$ profile
also shows a second local peak (around a depth of $13\,$\mathrm{p}\mathrm{c}$$
along the profile and at a depth of $\sim\,6\,$\mathrm{p}\mathrm{c}$$ from the
edge of the high density cloud) before sharply falling of. This also coincides
with the local peak in the column density as well as the rotational excitation
(third panel in Fig.6) profiles. But, the excitation temperature (first panel)
does not show a distinct peak. An additional peak also exists at a depth of
about $4\,$\mathrm{p}\mathrm{c}$$ along N. This along with the peak coincident
with the edge of the high density cloud appears to be part of a bubble shaped
structure in Fig.9. There is very little dense molecular material left around
the former peak and the diffuse gas does not appear to be impacted from the
feedback as can be seen from the excitation temperature profile corresponding
to this peak. Some pockets of higher column density gas appear to be
coincident with this peak. The feedback from the stars reported in Leistra et
al. (2005) which are located inside the bubble are most likely responsible for
this structure.

This 8 $\mu$\mathrm{m}$$ map was used as a template to identify regions of
feedback based on their integrated flux. In order to quantify the feedback
itself we assumed the 8 $\mathrm{\SIUnitSymbolMicro m}$ intensity to be a
proxy for the feedback by radiation, i.e. higher intensity corresponds to a
stronger feedback. The properties of the molecular CO emission were then
investigated in these feedback regions.

###  6.2 Molecular Gas Properties vs 8 $\mu$m Flux

In this section we investigate how the excitation temperature derived from
^12CO emission, the ^12CO 3–2/2–1 intensity ratio, and the ^13CO column
density vary with the degree of feedback traced by the integrated 8$\mu$m
flux. For this, the regions within a given interval of $8\leavevmode\nobreak\
$\mathrm{\SIUnitSymbolMicro m}$$ integrated flux were masked.

For every 8$\,\mu$\mathrm{m}$$ flux interval, we investigated the
aforementioned properties of the molecular emission of pixels within that
mask. Since the GLIMPSE image does not cover the whole range of latitude of
the LAsMA map, only the overlapping range of latitude was considered for the
analysis. Moreover, the blanked pixels in the excitation map were ignored. A
pixel scatter plot was then made for the 8$\,\mu$m flux versus each of the
three properties (see Fig.10). Only those pixels with S/N¿5 for all the
properties being investigated were considered. This also ensured that the
pixels with possible sub-thermal emission were avoided (these pixels are shown
as translucent gray scatter plots in the figure). The color of the scatter
points show the density of points in its vicinity. The mean values of the
properties are plotted as a function of 8$\,\mu$m flux on top of the pixel
scatter plot. A power-law function was then fitted to the mean values for all
the three properties and the results of the fits are also shown in the figure.
As is evident from Fig.10 excitation and rotational temperatures increase with
increasing 8$\,\mu$m flux. However, we only see a very modest increase in the
median column density values for higher 8$\,\mu$\mathrm{m}$$ flux.
Additionally, we also see a set of scatter points which have a much steeper
slope between 50 and 150 MJy.sr-1 for column density. This appears to be
mostly from the regions which are far away from the central stars and receive
very little feedback from them. Only one of these regions i.e.
G305.4399+00.2103 is known to be a diffuse H II region in literature (Urquhart
et al., 2014). The other regions could also be pre-stellar sources collapsing
under gravitation and therefore show high column densities. It is beyond the
scope of this paper to explore the reason for the observed trend at lower
8$\,\mu$m flux.

Figure 10: A pixel by pixel scatter plot of different gas properties versus
$8\,\mu$m flux. The colors represents the probability density of the scatter
points obtained by a kernel density estimate using Gaussian kernels. Overlaid
on top are the mean values of the quantity probed along with their standard
deviations plotted as a function of 8$\,\mu$m flux. The blue line shows the
power law fit to the mean values vs 8$\,\mu$m flux. The results of the fit are
shown at the top right corner of each panel. The gray translucent scatter
points in the excitation temperature plot (left) correspond to the pixels
which do not have a corresponding ^13CO detection and are not included in the
power law fit.

##  7 Dynamics of gas under feedback

In the preceding sections we have investigated the effects of feedback on the
morphology of the gas and its excitation. In this section we will investigate
the dynamical signature of this feedback. The shape of the spectrum in Fig. 3
is the sum of the spectra over all the pixels in the region. As has been seen
already, the G305 region consists of various clouds moving at different
velocities with respect to us. Additionally, the shape of the profile varies
from pixel to pixel. It is impossible to disentangle the contribution of the
line centroid velocities and the shape of the line profile from each pixel on
the overall shape of the profile in Fig. 3. In the following sections we will
try to study these line characteristics in a statistical way.

###  7.1 Velocity Centroid Probability Distribution Function

The probability distribution function (PDF) of velocities in observational or
simulated datasets can be used to characterize a cloud’s velocity structure.
PDFs can show the degree of intermittency in the turbulent molecular cloud
(Falgarone & Phillips, 1990) through the shapes of their wings. Increasing
intermittency causes a transition from Gaussian to exponential wings in
velocity PDFs. In this section, we estimate the velocity PDF of G305 in order
to reveal further effects of feedback on the molecular gas.

It is not possible to know the true velocity PDFs of the clouds from their
observations, owing to the fact that the complete velocity information is not
available for all three dimensions. Historically, two methods have been
employed to deduce the true velocity PDF from observational data of spectral
lines: Kleiner & Dickman (1985); Miesch & Bally (1994); Miesch et al. (1999);
Ossenkopf & Mac Low (2002) used the distribution of the line centroid
velocities to deduce the velocity PDFs. Alternatively, Falgarone & Phillips
(1990) estimated the velocity PDFs from high S/N observations of single line
profiles. Ossenkopf & Mac Low (2002) tested the realm of validity of both of
these approaches and concluded that if the size of the observed map is larger
or comparable to the depth of the cloud, the centroid velocity PDF reproduces
the correct velocity distribution. In contrast, for small maps, the average
line profiles comprise of a more comprehensive sampling of velocities, given
their more comprehensive line-of-sight sampling and hence, provide a better
approximation to the true velocity structure of the cloud.

The G305 complex is believed to have a flattened geometry (Hindson et al.,
2013) in the plane of the sky. Hence, instead of the average line profile
shown in Fig. 3, the centroid velocity PDF of the complex should be a good
tracer of the actual velocity distribution. An added benefit of using the
velocity centroid PDFs over using average line profiles is that local
phenomena such as outflows that could bias the determination of the global
velocity structure do not affect velocity centroid PDFs, since the broad wings
of their line profiles leave the centroid velocity unaffected.

The centroid velocity is effectively the moment-1 value of each pixel. Its
values were calculated from the ^12CO line using the formula,

$\frac{v_{c}}{$\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$}=\frac{\sum_{i=1}^{N_{chan}}T_{i}\cdot
v_{i}}{\sum_{i=1}^{N_{chan}}T_{i}}$ (9)

where, $N_{chan}$ is the total number of channels and $T_{i}$ is the observed
antenna temperature of the corresponding channel. Similarly to the moment-0
maps, only channels with signal greater than $5\sigma$ were included in the
calculation. Once the centroid velocity for each pixel was obtained, the PDF
was estimated using a normal histogram (i.e. the sum of the PDF $P$ is
normalized to unity). Pixels were partially weighted based on their S/N.
Pixels with a S/N greater than 100 were assigned an S/N of 100 in order to
prevent pixels with significant emission, with S/N $>$, say, 10 (but $<<100$)
to be unreasonably downweighted.

Figure 11: Probability density distribution of centroid velocities of ^12CO
for the G305 molecular cloud complex. The error bars are statistical errors
calculated as the square root of the histogram amplitudes.

Fig. 11 shows the centroid velocity PDF for the G305 complex. The shape of the
wings in the velocity PDF suggest that the velocity distribution in the
complex is not consistent with a Gaussian which would appear as a parabola on
a log-lin plot. To quantify the shape of the distribution we calculate its
statistical moments. The most frequently used moments are the mean ($\langle
v_{c}\rangle$), variance ($\sigma^{2}$), and the Kurtosis ($K$) of the
distribution defined as below:

$\displaystyle\frac{\langle
v_{c}\rangle}{$\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$}=\int_{-\infty}^{+\infty}dv_{c}P(v_{c})v_{c}$
(10)
$\displaystyle\frac{\sigma^{2}}{${\mathrm{km}}^{2}\text{\,}{\mathrm{s}}^{-2}$}=\int_{-\infty}^{+\infty}dv_{c}P(v_{c})[v_{c}-\langle
v_{c}\rangle]^{2}$ (11) $\displaystyle
K=\frac{1}{\sigma^{4}}\int_{-\infty}^{+\infty}dv_{c}P(v_{c})[v_{c}-\langle
v_{c}\rangle]^{4}.$ (12)

The variance is a measure of the total turbulent mixing energy. The Kurtosis
is a measure of the deviation from a Gaussian distribution. It assumes a value
of three for a Gaussian distribution and six for a distribution with
exponential wings. For our PDF we obtain the following values for the
aforementioned moments :

$\displaystyle\langle v_{c}\rangle=-37\pm
7\,$\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$$ $\displaystyle\sigma^{2}=4.0\pm
0.9\,${\mathrm{km}}^{2}\text{\,}{\mathrm{s}}^{-2}$$ $\displaystyle K=5.1\pm
1.0$

The Kurtosis of $5.1\pm 1.0$ indicates that the velocity PDF of the complex
has exponential wings. Using two-dimensional Burgers turbulence simulations,
neglecting pressure forces, Chappell & Scalo (2001) showed that the velocity
PDFs are Gaussian for models of decaying turbulence and have exponential wings
for models driven by strong stellar winds.

###  7.2 Stacked Spectra

Figure 12: Stacked spectra of ^12CO(J=3–2) emission corresponding to the
inside- (translucent red) and outside feedback zones (translucent blue) for
different choices of GLIMPSE 8$\,\mu$\mathrm{m}$$ flux thresholds (specified
on top of each sub-plot). Each sub-plot consists of 500 stacked spectra each
for both zones obtained by randomly selecting the square root of the total
number of pixels from each zone. The black and golden spectra for each zone
were obtained by calculating the median value for each channel over the 500
iterations performed. The black (golden) dotted line in all the sub-plots
correspond to the position of peak emission of the median stacked spectra
inside (outside) the feedback zone corresponding to the threshold of
$40\,$\mathrm{MJy}\text{\,}{\mathrm{sr}}^{-1}$$. Figure 13: Variance (left
panel), skewness (middle panel) and Kurtosis (right panel) of stacked spectra
corresponding to inside- (black dots with red bars) and outside feedback zones
(golden dots with blue bars) in Fig. 12 as a function of GLIMPSE
8$\,\mu$\mathrm{m}$$ flux thresholds. The dots represent the median value and
the bars span the 25 to 75 percentile spread of values from the 500 iterations
for each threshold value.

The velocity centroid PDFs as seen in Sect. 7.1 contain information only about
the central velocity of the gas. In this section we investigate the effect of
feedback on the line profiles of the G305 molecular cloud complex, especially
whether the shape of the line profile in the regions where we expect feedback
to be present is significantly different from those where we see little
evidence of feedback. We also try to characterize the deviations, if any, as a
function of the strength of the feedback.

We used the same method as in section 6.2 to quantify the strength of the
feedback. Different 8$\,\mu$\mathrm{m}$$ intensities were logarithmically
distributed. These values were used as a threshold to create masks on the G305
region. Regions with 8$\,\mu$\mathrm{m}$$ flux greater than the threshold were
labeled as inside feedback zone and those outside were labeled outside
feedback zone. All the maps were reprojected onto the same two dimensional
grid over the galactic longitude and latitude. All the spectra were then
translated to a common central velocity based on their velocity centroids (see
section 7.1 for how to calculate the velocity centroids). After aligning, a
number of pixels equal to the square root of the total pixels in the
respective zones were randomly selected. For these randomly chosen pixels the
spectra were averaged to obtain an average spectrum representing the inside-
and outside feedback zones. The spectra obtained by this method will be
referred to as average stacked spectrum from now on. This process was then
repeated 500 times to avoid any biases and obtain a more representative set of
spectra for each region.

Fig. 12 shows the stacked spectra corresponding to the inside- and outside
feedback zones for the G305 molecular cloud complex. We also derived a median
stacked spectrum for each zone corresponding to all thresholds. This was
obtained by calculating the median value for each channel over the 500
iterations performed. A few things become evident from Fig. 12. The spectra
from the inside feedback zones are brighter than outside feedback zones. With
increasing feedback strength the peaks of the former also get brighter
indicating that with stronger feedback more gas gets excited to the higher $J$
transitions. There is not much overlap between the individual stacked spectra
from the outside- and inside feedback zones. Hence, the median profiles for
the two regions for each threshold which look very different from each other
are indeed representative of the actual differences between the two regions
and are not in fact biased by any individual stacked spectra. This was also
confirmed by running a Kolmogorov-Smirnov (KS) test (Kolmogorov, 1933;
Smirnov, 1939) between the spectra inside and outside the thresholds. We
placed $p<0.05$ constraint to reject the null hypothesis that the spectra are
drawn from the same population. The p-value measures the probability of random
chance being responsible for the observed difference between the two spectra.
The test rejected the null hypothesis with overwhelming certainty
($p<10^{-5}$). The median stacked spectrum from the inside feedback zones
appear to be blue shifted compared to that from the outside feedback zones.
This is an consequence of the translation of the spectra to a common velocity
using their moment-1 values. The spectra inside the feedback zones have a peak
component that is at the same velocity as that outside the feedback zone. But
in addition the feedback from the stars seems to have pushed some gas away
from us which shows up as the broad positively skewed part of the spectrum
inside the feedback zone. This makes the moment-1 value of the overall
spectrum to be redshifted from the true peak of the spectrum. Consequently, in
the process of aligning all spectra along their moment-1 value, those inside
the feedback zone appear to be blue shifted. Thus, the apparent blue shift of
the stacked spectra from inside the feedback zone is evidence of the stellar
feedback pushing gas away from us.

In order to characterize the stacked spectra in Fig. 12 we calculated their
statistical moments. The moments used for these profiles are the variance
($\sigma^{2})$, skewness (S), and Kurtosis (K) :

$\displaystyle\frac{\sigma^{2}}{${\mathrm{km}}^{2}\text{\,}{\mathrm{s}}^{-2}$}=\left(\int_{-\infty}^{+\infty}dvP(v)[v-\langle
v\rangle]^{2}\right)/\left(\int_{-\infty}^{+\infty}dvP(v)\right)$ (13)
$\displaystyle
S=\frac{1}{\sigma^{3}}\cdot\left(\int_{-\infty}^{+\infty}dvP(v)[v-\langle
v\rangle]^{3}\right)/\left(\int_{-\infty}^{+\infty}dvP(v)\right)$ (14)
$\displaystyle
K=\frac{1}{\sigma^{4}}\cdot\left(\int_{-\infty}^{+\infty}dvP(v)[v-\langle
v\rangle]^{4}\right)/\left(\int_{-\infty}^{+\infty}dvP(v)\right)$ (15)

Here, $P(v)$ is the antenna temperature of the spectrum at the velocity $v$,
and $\langle v\rangle$ is the expectation value for the velocity of the
spectrum given by $\langle
v\rangle=\left(\int_{-\infty}^{+\infty}dvP(v)v\right)/\left(\int_{-\infty}^{+\infty}dvP(v)\right)\,$\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$$.

Fig. 13 demonstrates how these moments depend on the choice of the
8$\,\mu$\mathrm{m}$$ flux threshold. A few things stand out from this result.
We expect turbulence to result in broader line profiles. But contrary to
expectations, the variance of the average stacked spectra from the inside
feedback zones are mostly smaller than that from the outside feedback zone.
For the outside feedback zones the variance decreases until $\sim
80\,$\mathrm{MJy}\text{\,}{\mathrm{sr}}^{-1}$$ and then stays constant with
increasing threshold. Looking at the variances of average stacked spectra for
the inside feedback zones, we observe that the variance stays constant
irrespective of the choice of threshold until $\sim
180\,$\mathrm{MJy}\text{\,}{\mathrm{sr}}^{-1}$$ when it starts decreasing. We
observe that the stacked spectra are consistently more skewed inside the
feedback regions than outside irrespective of the choice of threshold. A
positive skewness implies that the profile’s red wing is enhanced compared to
the blue wing. As explained before, this hints at the gas being pushed away
from us. For small threshold values, the stacked spectra in outside feedback
zones have skewness close to zero. But, it increases with increasing threshold
levels. Kurtosis of the stacked spectra in the inside feedback zones are
mostly larger than those in the outside feedback zone indicating that the
profiles have more pronounced wings for the gas impacted with feedback. For
8$\,\mu$\mathrm{m}$$ flux thresholds above $\sim
180\,$\mathrm{MJy}\text{\,}{\mathrm{sr}}^{-1}$$, the Kurtosis of the spectra
inside the feedback zone increases. For very high threshold values the
Kurtosis shows a large spread. These regions correspond to those very close to
the UC HII regions and hence show that the feedback in these regions is very
effective at pushing gas away. This is also evident from the stacked spectra
in Fig.12 where secondary peaks are clearly visible showing gas clumps being
pushed out. The Kurtosis of the spectra outside the feedback zone almost stays
in the same range. We also observed that the trend followed by the Kurtosis is
exactly opposite to the one followed by the variances for both inside and
outside feedback zones. When the variances of stacked spectra decrease, the
Kurtosis increases and vice versa.

###  7.3 Stacked Spectra for 8$\,\mu$\mathrm{m}$$ Flux Intervals

Figure 14: Stacked Spectra for regions corresponding to different choices of
GLIMPSE 8$\,\mu$\mathrm{m}$$ flux intervals. Each interval sub-plot consists
of 500 stacked spectra (translucent blue), each corresponding to randomly
selected pixels from the region. The golden spectra in each sub-plot
corresponds to the median spectra for that interval obtained by taking the
median channel intensity for each channel. The interval values are given on
top of each sub-plot. Figure 15: Variance (left panel), skewness (middle
panel) and Kurtosis (right panel) of stacked spectra corresponding to GLIMPSE
8$\,\mu$\mathrm{m}$$ flux intervals in Fig. 14 as a function of the median
8$\,\mu$\mathrm{m}$$ flux for that interval. The golden circles represent the
median of the distribution and the blue lines span the 5 to 95 percentile
range of values for each set of 500 iterations per interval.

In the preceding section, the stacked spectra inside the feedback zone for a
given threshold include the cumulative sum of the contributions from all
pixels with 8$\,\mu$\mathrm{m}$$ flux greater than the threshold value. It
becomes difficult to identify the spectra representative of a given interval
of 8$\,\mu$\mathrm{m}$$ flux. For this, we decided to investigate the stacked
spectra corresponding to intervals of 8$\,\mu$\mathrm{m}$$ flux. Pixels
corresponding to the flux intervals were masked and their stacked spectra were
derived by randomly picking pixels corresponding to each mask, similar to that
done in Sec.7.2. The process was repeated 500 times. A median spectrum was
derived from the set of 500 stacked spectra corresponding to each mask by
taking the median intensity of each channel.

Fig. 14 shows the stacked spectra corresponding to the pixels in
8$\,\mu$\mathrm{m}$$ flux intervals. The peaks of the profiles do increase
with increasing flux as expected. In order to look at their properties we
calculated the statistical moments of each of the stacked spectra using Eq.13
– 15. Their median along with the 5 to 95 percentile range of values spanned
by the spread were then plotted as a function of the median value of the
8$\,\mu$\mathrm{m}$$ flux interval. Fig. 15 shows the statistical moments as a
function of 8$\,\mu$\mathrm{m}$$ flux. The standard deviation initially
decreases with increasing 8$\,\mu$\mathrm{m}$$ flux but starts increasing with
flux from $\sim 100\,$\mathrm{MJy}\text{\,}{\mathrm{sr}}^{-1}$$ up until $\sim
215\,$\mathrm{MJy}\text{\,}{\mathrm{sr}}^{-1}$$. After this the standard
deviation of the stacked spectra decreases. The Kurtosis of the stacked
spectra show the exact opposite trends to the standard deviation: where if the
standard deviation decreases, the Kurtosis increases and vice versa. At the
lowest range of probed 8$\,\mu$\mathrm{m}$$ flux the stacked spectra seem to
have a skewness approaching 0 and a Kurtosis close to 3, which hints at a
Gaussian shape of its profile. The skewness of the stacked spectra then
increases to 0.6 for an 8$\,\mu$\mathrm{m}$$ flux of $\sim
100\,$\mathrm{MJy}\text{\,}{\mathrm{sr}}^{-1}$$, while it increases only a
little (to 0.8) for higher values, around $\sim
600\,$\mathrm{MJy}\text{\,}{\mathrm{sr}}^{-1}$$.

To investigate possible causes for the trends we find in the statistical
moments of the stacked spectra, we plotted the contours of
8$\,\mu$\mathrm{m}$$ flux on top of ^13CO integrated intensity map. The
relevant 8$\,\mu$\mathrm{m}$$ flux values at which the statistical moments
change directions are 84, 123, 178, 260 and 378
$\mathrm{MJy}\text{\,}{\mathrm{sr}}^{-1}$. Fig. 16 shows these contours
overlaid on top of the ^13CO moment 0 map. Almost all of the dense gas traced
by the ^13CO is contained inside the
$123\,$\mathrm{MJy}\text{\,}{\mathrm{sr}}^{-1}$$ contour. We expect the
feedback from the central clusters to be deposited on the surface of the dense
gas. As we examine the higher flux contours, they appear to surround the HII
and UC HII regions in the complex (Hindson et al., 2012). It is possible that
the high column density gas surface interacting with the feedback from the
central clusters is responsible for the observed increase in skewness and
Kurtosis and the decrease in the standard deviation at $\sim
100\,$\mathrm{MJy}\text{\,}{\mathrm{sr}}^{-1}$$, as this is where we expect
the feedback from the central stars to be deposited. As the
8$\,\mu$\mathrm{m}$$ flux increases, the gas is impacted mostly by the stellar
winds and ionizing radiation from embedded HII and UC HII regions which
appears to be responsible for the increase in skewness as well as kurtosis and
quite interestingly, the decrease in standard deviation of the stacked line
profiles. The ^13CO emission from our observation suffers from a lack of
completeness as we do not sample a lot of low column density gas for a given
8$\,\mu$\mathrm{m}$$ flux. Most of the spectra outside the masks are dominated
by noise. In addition, the wings of the line profiles are also dominated by
noise in many cases even when they are significantly detected in ^12CO. Since,
these wings correspond to the gas being expelled, it is difficult to trace
them using ^13CO. Due to these reasons, it was not possible to repeat the
stacked spectra analyses with ^13CO lines to gain any further insights into
the causes of the observed trends. Examining the literature, we would like to
emphasize that apparently this kind of analysis has not yet been performed,
neither on any actual nor on simulated observations of molecular cloud
complexes undergoing feedback. So far, this is a stand alone result and it
needs to be seen if these observed trends in stacked spectra (if real) are
unique to G305 or occur in other GMCs as well before making any meaningful
speculations on the causes of these trends.

Figure 16: ^13CO $J=3\text{-}2$ moment 0 map with GLIMPSE 8$\,\mu$\mathrm{m}$$
contours corresponding to 84(purple), 123(brown), 178(blue), 260(green) and
550.(orange) $\mathrm{MJy}\text{\,}{\mathrm{sr}}^{-1}$ overlaid on top. The
HII and UC HII regions are marked by cyan triangles and red diamonds
respectively.

##  8 Summary

We observed the G305 star forming giant molecular cloud with the APEX
telescope in the ^12CO and ^13CO $J=3\text{-}2$ transitions in order to study
the effects of feedback from the hot, luminous stars at the center of the
complex on the molecular gas. We summarize our finding below:

  * •

The central region of the complex has been cleared out of most of the high
column density gas as traced by the ^13CO emission. The calculations of energy
input from the visible stars in the complex showed that they have enough
energy input to drive the size of the cavity observed if the electron density
($n_{e}$) in the region is less than $500\,${\mathrm{cm}}^{-3}$$. A sequential
formation of Danks 2 followed by Danks 1 and the other stars in the complex
can explain the size of the observed cavity.

  * •

^12CO excitation temperature and ^13CO column density maps of the region were
produced under the assumption of LTE. Ratio maps of the rotational excitation
were also made using ^13CO $J=2\text{-}1$ data from SEDIGISM and our ^13CO
$J=3\text{-}2$ data. The validity of LTE assumption was also tested and it was
concluded that regions with simultaneous emission from both ^12CO and ^13CO
are most likely in LTE.

  * •

Excitation temperature maps as well as ratio maps of the rotational excitation
show that the feedback is being deposited in a narrow region at the edge of
the dense gas facing the central stellar complex heating it up. The gas then
shows a decline in temperature as one moves away from the center. The column
density also shows a marked increase at the edge of the denser gas, but unlike
the excitation temperature, does not always decrease drastically as one moves
away from the center.

  * •

Line profiles along two directions were chosen at random to test if the energy
input from the stars is responsible for this increased excitation of the gas.
For the profile towards the north of the complex $\sim 61\%$ of the radiation
pressure from the nearby stars is being used up to heat and compress the gas
at the surface of the cloud; whereas for that towards the south of the
complex, $<14.5\%$ of the input radiation pressure from the star is going
towards heating the gas.

  * •

The GLIMPSE 8$\,\mu$\mathrm{m}$$ flux, which is dominated by FUV-excited PAH
emission, was used as a proxy to the feedback strength. The regions with
higher 8$\,\mu$\mathrm{m}$$ flux have higher median excitation temperatures,
^13CO column density as well as a higher median ^13CO
$J=3\text{-}2/2\text{-}1$ ratio.

  * •

Investigating the impact of feedback on the dynamics of the gas showed that
the centroid velocity probability distribution function of the pixels in the
region showed exponential wings indicative of turbulence driven by strong
stellar feedback.

  * •

This was followed by stacking the spectra of the pixels and plotting the
average stacked profiles. On assuming a certain 8$\,\mu$\mathrm{m}$$ flux
threshold, the stacked spectra with 8$\,\mu$\mathrm{m}$$ flux above this
threshold (assumed to indicate stronger feedback) showed systematically more
skewed line profiles than the stacked spectra representing regions with
8$\,\mu$\mathrm{m}$$ flux less than the threshold. The stacked spectra of
regions with stronger feedback on an average had narrower but much more winged
profiles when compared to those from regions with weaker feedback. This
positive skew is most likely indicative of parts of the cloud complex being
pushed away from us, which results in a positive wing of the overall stacked
spectra. We also note that the standard deviation and the kurtosis of the
stacked profiles show opposing trends when plotted as a function of
8$\,\mu$\mathrm{m}$$ flux.

###### Acknowledgements.

We thank the staff of the APEX telescope for their assistance in observations.
We also thank the anonymous referee whose invaluable suggestions have
significantly improved the quality of the paper. This work acknowledges
support by The Collaborative Research Council 956, sub-project A6, funded by
the Deutsche Forschungsgemeinschaft (DFG). DC acknowledges support by the
German _Deutsche Forschungsgemeinschaft, DFG_ project number SFB956A. Parts of
this work are based on observations made with the Spitzer Space Telescope,
which is operated by the Jet Propulsion Laboratory (JPL), California Institute
of Technology under a contract with NASA. This publication also made use of
data products from the Midcourse Space Experiment. Processing of the data was
funded by the Ballistic Missile Defense Organization with additional support
from NASA Office of Space Science. This research has also made use of the
NASA/ IPAC Infrared Science Archive, which is operated by the JPL, under
contract with NASA.

## References

  * Allamandola et al. (1989) Allamandola, L. J., Tielens, A. G. G. M., & Barker, J. R. 1989, ApJS, 71, 733
  * André (2017) André, P. 2017, Comptes Rendus Geoscience, 349, 187
  * Benjamin et al. (2003) Benjamin, R. A., Churchwell, E., Babler, B. L., et al. 2003, PASP, 115, 953
  * Bertoldi (1989) Bertoldi, F. 1989, ApJ, 346, 735
  * Borissova et al. (2019) Borissova, J., Roman-Lopes, A., Covey, K., et al. 2019, AJ, 158, 46
  * Chappell & Scalo (2001) Chappell, D. & Scalo, J. 2001, MNRAS, 325, 1
  * Churchwell et al. (2009) Churchwell, E., Babler, B. L., Meade, M. R., et al. 2009, PASP, 121, 213
  * Clark & Porter (2004) Clark, J. S. & Porter, J. M. 2004, A&A, 427, 839
  * Crowther (2007) Crowther, P. A. 2007, ARA&A, 45, 177
  * Davies et al. (2012) Davies, B., Clark, J. S., Trombley, C., et al. 2012, MNRAS, 419, 1871
  * Deharveng et al. (2010) Deharveng, L., Schuller, F., Anderson, L. D., et al. 2010, A&A, 523, A6
  * Faimali et al. (2012) Faimali, A., Thompson, M. A., Hindson, L., et al. 2012, MNRAS, 426, 402
  * Falgarone & Phillips (1990) Falgarone, E. & Phillips, T. G. 1990, ApJ, 359, 344
  * Fazio et al. (2004) Fazio, G. G., Hora, J. L., Allen, L. E., et al. 2004, ApJS, 154, 10
  * Garay & Lizano (1999) Garay, G. & Lizano, S. 1999, PASP, 111, 1049
  * Green et al. (2009) Green, J. A., Caswell, J. L., Fuller, G. A., et al. 2009, MNRAS, 392, 783
  * Green et al. (2012) Green, J. A., Caswell, J. L., Fuller, G. A., et al. 2012, MNRAS, 420, 3108
  * Güsten et al. (2008) Güsten, R., Baryshev, A., Bell, A., et al. 2008, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 7020, Proc. SPIE, 702010
  * Güsten et al. (2006) Güsten, R., Nyman, L. Å., Schilke, P., et al. 2006, A&A, 454, L13
  * Hindson et al. (2010) Hindson, L., Thompson, M. A., Urquhart, J. S., Clark, J. S., & Davies, B. 2010, MNRAS, 408, 1438
  * Hindson et al. (2012) Hindson, L., Thompson, M. A., Urquhart, J. S., et al. 2012, MNRAS, 421, 3418
  * Hindson et al. (2013) Hindson, L., Thompson, M. A., Urquhart, J. S., et al. 2013, MNRAS, 435, 2003
  * Kim & Koo (2001) Kim, K.-T. & Koo, B.-C. 2001, ApJ, 549, 979
  * Kleiner & Dickman (1985) Kleiner, S. C. & Dickman, R. L. 1985, ApJ, 295, 466
  * Kolmogorov (1933) Kolmogorov, A. 1933, Inst. Ital. Attuari, Giorn., 4, 83
  * Krumholz et al. (2014) Krumholz, M. R., Bate, M. R., Arce, H. G., et al. 2014, in Protostars and Planets VI, ed. H. Beuther, R. S. Klessen, C. P. Dullemond, & T. Henning, 243
  * Leistra et al. (2005) Leistra, A., Cotera, A. S., Liebert, J., & Burton, M. 2005, AJ, 130, 1719
  * Lumsden et al. (2013) Lumsden, S. L., Hoare, M. G., Urquhart, J. S., et al. 2013, ApJS, 208, 11
  * Mauerhan et al. (2011) Mauerhan, J. C., Van Dyk, S. D., & Morris, P. W. 2011, AJ, 142, 40
  * Miesch & Bally (1994) Miesch, M. S. & Bally, J. 1994, ApJ, 429, 645
  * Miesch et al. (1999) Miesch, M. S., Scalo, J., & Bally, J. 1999, ApJ, 524, 895
  * Milam et al. (2005) Milam, S. N., Savage, C., Brewster, M. A., Ziurys, L. M., & Wyckoff, S. 2005, ApJ, 634, 1126
  * Motte et al. (2018) Motte, F., Bontemps, S., & Louvet, F. 2018, ARA&A, 56, 41
  * Muders et al. (2006) Muders, D., Hafok, H., Wyrowski, F., et al. 2006, A&A, 454, L25
  * Ossenkopf & Mac Low (2002) Ossenkopf, V. & Mac Low, M. M. 2002, A&A, 390, 307
  * Panagia (1973) Panagia, N. 1973, AJ, 78, 929
  * Pardo et al. (2001) Pardo, J. R., Cernicharo, J., & Serabyn, E. 2001, IEEE Transactions on Antennas and Propagation, 49, 1683
  * Pellegrini et al. (2007) Pellegrini, E. W., Baldwin, J. A., Brogan, C. L., et al. 2007, ApJ, 658, 1119
  * Polehampton et al. (2019) Polehampton, E., Hafok, H., & Muders, D. 2019, APEX Calibration and Data Reduction Manual, Atacama Pathfinder EXperiment (APEX), aPEX Report APEX-MPI-MAN-0012, Revision 1.3
  * Rathborne et al. (2002) Rathborne, J. M., Burton, M. G., Brooks, K. J., et al. 2002, MNRAS, 331, 85
  * Schöier et al. (2005) Schöier, F. L., van der Tak, F. F. S., van Dishoeck, E. F., & Black, J. H. 2005, A&A, 432, 369
  * Schuller et al. (2017) Schuller, F., Csengeri, T., Urquhart, J. S., et al. 2017, A&A, 601, A124
  * Shara et al. (2009) Shara, M. M., Moffat, A. F. J., Gerke, J., et al. 2009, AJ, 138, 402
  * Smirnov (1939) Smirnov, N. V. 1939, Bull. Math. Univ. Moscou, 2, 3
  * Sugitani & Ogura (1994) Sugitani, K. & Ogura, K. 1994, ApJS, 92, 163
  * Thompson et al. (2004) Thompson, M. A., Urquhart, J. S., & White, G. J. 2004, A&A, 415, 627
  * Tielens (2008) Tielens, A. G. G. M. 2008, ARA&A, 46, 289
  * Tielens & Hollenbach (1985) Tielens, A. G. G. M. & Hollenbach, D. 1985, ApJ, 291, 722
  * Ulich & Haas (1976) Ulich, B. L. & Haas, R. W. 1976, ApJS, 30, 247
  * Urquhart et al. (2014) Urquhart, J. S., Figura, C. C., Moore, T. J. T., et al. 2014, MNRAS, 437, 1791
  * Watkins et al. (2019) Watkins, E. J., Peretto, N., Marsh, K., & Fuller, G. A. 2019, A&A, 628, A21
  * Wilson et al. (2013) Wilson, T. L., Rohlfs, K., & Hüttemeister, S. 2013, Tools of Radio Astronomy
  * Zinnecker & Yorke (2007) Zinnecker, H. & Yorke, H. W. 2007, ARA&A, 45, 481

##  Appendix A Noise and Offset Details

Table 1: Position and Noise towards off-positions used in otf-mapping of G305.

RA [J2000] | Dec [J2000] | Freq.-Range [GHz] | Noise rms [K]aa$a$The rms noise was obtained by averaging over all 7 pixels, albeit being at different offsets with respect to the position mentioned in the table.
---|---|---|---
13:08:23.90 | -60:48:13.0 | 330.50-330.65 | 1.001e-2
|  | 345.70-345.85 | 1.068e-2
13:10:52.20 | -64:47:37.0 | 330.50-330.65 | 1.984e-2
|  | 345.70-345.85 | 1.884e-2
13:20:12.00 | -64:42:01.0 | 330.50-330.65 | 2.116e-2
|  | 345.70-345.85 | 2.077e-2
13:16:33.30 | -60:43:19.0 | 330.50-330.65 | 2.357e-2
|  | 345.70-345.85 | 2.176e-2
555

Figure 17: Pixel wise noise maps of ^12CO(3-2) (top) and ^13CO(3-2) (bottom)
of the G305 GMC complex.