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 : II. Effect of feedback on clump properties

P. Mazumdar High resolution LAsMA 12CO and 13CO observation of the G305 giant
molecular cloud complex : II. Effect of feedback on clump propertiesHigh
resolution LAsMA 12CO and 13CO observation of the G305 giant molecular cloud
complex : II. Effect of feedback on clump properties F. Wyrowski High
resolution LAsMA 12CO and 13CO observation of the G305 giant molecular cloud
complex : II. Effect of feedback on clump propertiesHigh resolution LAsMA 12CO
and 13CO observation of the G305 giant molecular cloud complex : II. Effect of
feedback on clump properties J. S. Urquhart High resolution LAsMA 12CO and
13CO observation of the G305 giant molecular cloud complex : II. Effect of
feedback on clump propertiesHigh resolution LAsMA 12CO and 13CO observation of
the G305 giant molecular cloud complex : II. Effect of feedback on clump
properties D. Colombo High resolution LAsMA 12CO and 13CO observation of the
G305 giant molecular cloud complex : II. Effect of feedback on clump
propertiesHigh resolution LAsMA 12CO and 13CO observation of the G305 giant
molecular cloud complex : II. Effect of feedback on clump properties K. M.
Menten High resolution LAsMA 12CO and 13CO observation of the G305 giant
molecular cloud complex : II. Effect of feedback on clump propertiesHigh
resolution LAsMA 12CO and 13CO observation of the G305 giant molecular cloud
complex : II. Effect of feedback on clump properties S. Neupane High
resolution LAsMA 12CO and 13CO observation of the G305 giant molecular cloud
complex : II. Effect of feedback on clump propertiesHigh resolution LAsMA 12CO
and 13CO observation of the G305 giant molecular cloud complex : II. Effect of
feedback on clump properties M. A. Thompson High resolution LAsMA 12CO and
13CO observation of the G305 giant molecular cloud complex : II. Effect of
feedback on clump propertiesHigh resolution LAsMA 12CO and 13CO observation of
the G305 giant molecular cloud complex : II. Effect of feedback on clump
properties

(Received xxx / Accepted xxx)

###### Abstract

Context. Understanding the effect of feedback from young massive stars on the
star forming ability of their parental 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 whether feedback from the central OB stars were
triggering star formation in G305 or actually disrupting this process.

Methods. The region was decomposed into clumps using dendrogram analysis. A
catalog of the clump properties such as their positions, luminosities, masses,
radii, velocity dispersions, volume densities, surface mass densities, etc.
was created. The surface mass densities of the clumps were plotted as a
function of the incident 8 $\mu$m flux. A mask of the region with 8 $\mu$m
flux $>100\,$MJy/sr was created and clumps were categorized into three classes
based on their extent of overlap with the mask, namely “mostly inside” (¿67%
overlap), “partly inside” (¿10% and ¡67% overlap), and “outside” (¡10%
overlap). The surface mass density distribution of each of these populations
was separately plotted. This was followed by comparing the G305 clumps with
the Galactic average taken from a distance limited sample of ATLASGAL and
CHIMPS clumps. Finally, the cumulative distribution functions (CDF) of the
clump masses in G305 and their $L/M$ ratios were compared to that of the
Galactic sample to determine which mechanism of feedback was dominant in G305.

Results. The surface mass densities of clumps showed a positive correlation
with the incident 8 $\mu$m flux. The data did not have sufficient velocity
resolution to discern the effects of feedback on the linewidths of the clumps.
The sub-sample of clumps named “mostly inside” had the highest median surface
mass densities followed by the “partly inside” and “outside” sub-samples. The
difference between the surface mass density distribution of the three sub-
samples were shown to be statistically significant using the KS test. The
“mostly inside” sample also showed the highest level of fragmentation compared
to the other two sub-samples. These prove that the clumps inside the G305
region are triggered. The G305 clump population is also statistically
different from the Galactic average population, the latter approximating that
of a quiescent population of clumps. This provided further evidence that
redistribution was not a likely consequence of feedback on the GMC. The CDFs
of clump masses and their $L/M$ ratios are both flatter than that of the
Galactic average, indicating that clumps are heavier and more efficient at
forming stars in G305 compared to the Galactic average.

Conclusions. Feedback in G305 has triggered star formation. The collect and
collapse method is the dominant mechanism at play in G305.

###### Key Words.:

Submillimeter: ISM – ISM:structure – ISM: evolution – Stars: formation –
methods: analytical – techniques: image processing

##  1 Introduction

G305 is one of the most massive and luminous star forming giant molecular
clouds (GMC) in the Milky Way (Clark & Porter (2004), Fig. 1). It is located
$\sim\,4\,$\mathrm{k}\mathrm{p}\mathrm{c}$$ (Clark & Porter, 2004; Davies et
al., 2012; Borissova et al., 2019) away from us at $l\sim$$\,,\,b\sim$$$ in
the Scutum-Crux spiral arm of the Galactic plane. Its center has been cleared
of the interstellar molecular gas by the stellar winds and the ionizing front
originating from massive stars belonging to two visible central clusters
(Danks 1 and 2) consisting of 21 OB stars and the Wolf-Rayet star (WR48a)
(Clark & Porter, 2004; Davies et al., 2012). A diffuse population of evolved
massive stars has also been found to exist inside the cavity with ages similar
to that of 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). The central cavity is also filled with ionized gas as shown by
radio continuum observations by Hindson et al. (2012). Surrounding the central
cavity is a thick layer of molecular gas (Hindson et al., 2010, 2013; Mazumdar
et al., 2021). Star formation tracers (water and methanol masers, HII and
ultracompact (UC) HII regions and massive young stellar objects (MYSOs)) have
also been reported by multiple studies (Clark & Porter, 2004; Hindson et al.,
2012; Lumsden et al., 2013; Urquhart et al., 2014a; Green et al., 2009, 2012).
Figure 1 shows a three-color composite image of G305 highlighting three
aspects of the complex. The 21.3 $\mu$m Midcourse Space Experiment (MSX)
(Price et al., 2001) image is shown in red and traces the hot dust being
heated by the OB stars within the cavity and towards the edges where the
ionization front is interacting with the surrounding molecular gas. The cold
molecular gas traced by the integrated 13CO ($3\rm{-}2$) line emission
(Mazumdar et al., 2021, referred to as Paper I from here on) can be seen in
blue being shrouded by emission from the 8 $\mu$m filter of the Spitzer
Infrared array camera (IRAC) (Churchwell et al., 2009) shown in green. The
latter traces the polycyclic aromatic hydrocarbons (PAHs) whose emission is
excited by the far-UV photons emanating from the stars in the central cavity.

Figure 1: Three-color image (green = Spitzer-IRAC4 8 $\mu\rm{m}$, red =
Midcourse Space Experiment (MSX) 21.3 $\mu\rm{m}$, blue = LAsMA (^13CO(3-2)
moment-0)) 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
^13CO(3-2) line 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 white circles respectively, and the wolf-rayet star
WR48a has been marked as a white star.

The role played by feedback from high mass stars ($M>8\,\rm{M_{\odot}}$) on
their surrounding interstellar medium (ISM) has been a subject of active
research. As is the case in G305, these stars exist in massive clusters
located inside GMCs (Motte et al., 2018). They inject energy and momentum into
their natal clouds via very strong stellar winds, ionizing radiation and
eventually, supernovae (Krumholz et al., 2014). Such feedback from OB stars
can potentially enhance and/or disrupt the formation of subsequent generations
of stars (Krumholz et al., 2014; Deharveng et al., 2010), consequently playing
a vital role in the evolution of GMCs (Zinnecker & Yorke, 2007). The G305
region, being a very extensively studied GMC, is a very good candidate to
examine the effects of feedback on the GMC. Although, circumstantial evidences
of triggering in G305 exists (Clark & Porter, 2004; Hindson et al., 2010), it
has, as yet, not been definitively proven.

We observed G305 with the Atacama Pathfinder EXperiment (APEX) telescope to
examine what effect this feedback from the central population of stars has on
the molecular gas content of the GMC (Paper I). The molecular gas in the GMC
was mapped in the 12CO and 13CO ($3\rm{-}2$) lines. The temperature and column
density of the gas facing the center of the cavity was found to be at least a
factor of 2 higher than that of the part of the cloud facing away from it,
demonstrating that the gas impacted by feedback gets heated and compressed and
in turn shields the layers behind it. The rotational excitation of the gas
traced by the $3\rm{-}2$/$2\rm{-}1$ 13CO line ratios showed similar
enhancements at the edge of the cloud facing the center. Using 8 $\mu$m flux
of the region as a proxy to the feedback strength, we demonstrated that
regions experiencing feedback had higher median excitation temperatures,
rotational excitation, and column density. Examination of the probability
distribution function (PDF) of the centroid velocities revealed exponential
wings and a stacked spectral analysis also revealed the emission profiles to
be positively skewed (which we hypothesized was indicative of the gas being
pushed away from us), all of which is consistent with the hypothesis that star
formation has been triggered.

Having investigated the effects of feedback on the GMC as a whole, we are now
interested in exploring the effects of feedback on the ability of the GMC to
form subsequent generations of stars. GMCs show a hierarchical structure with
clouds condensing into clumps that condense and fragment into cores,
eventually forming stars (Blitz & Stark, 1986; Lada, 1992). Since clumps
provide the environment and the raw material for star formation, the impact of
feedback on the future generation of stars can be studied by their effect on
the clump properties in a GMC. In this paper we will decompose the molecular
emission distribution in G305 into clumps and investigate their properties in
an effort to study how feedback has affected clump properties and whether the
observed star-formation has been triggered.

A broad classification of the effects of feedback on star-formation can lead
to three different scenarios which we outline here:

  1. 1.

Redistribution: The expansion of an HII region simply moves the star forming
clumps to its edge. The molecular cloud is already seeded with dense clumps
that would collapse to form stars. An apparent enhancement of star formation
observed on the periphery of the HII region is not necessarily caused by the
HII region. However, overall star formation has not been enhanced. We call
this the “redistribution” scenario.

  2. 2.

Dispersion: In high mass star forming regions feedback is very strong and can
simply disperse most of the molecular material via various mechanisms
(Krumholz et al., 2014, and references therein), thereby suppressing the
ability of the GMC to form stars. We call this the “dispersion” scenario.

  3. 3.

Triggering: In this case, the feedback from the stars actually enhances or
induces star-formation in the natal cloud. Many mechanisms are known or
hypothesized to be responsible for triggering, e.g. supernovae (de Geus, 1992;
Nagakura et al., 2009, and references therein), cloud-cloud collisions (for a
comprehensive review, see Fukui et al., 2021), collect and collapse (Elmegreen
& Lada, 1977; Dale et al., 2007), radiation driven implosion (Bertoldi, 1989;
Bertoldi & McKee, 1990; Kessel-Deynet & Burkert, 2003; Lee & Chen, 2007). In
G305, there has been an indication of the “collect and collapse” (C&C)
mechanism playing a role in triggering star formation (Hindson et al., 2010).
The C&C model was first proposed by Elmegreen & Lada (1977). In this scenario,
the expanding warm ionized gas sweeps up a shell of shocked cool neutral gas.
This compressed and shocked layer may become gravitationally unstable along
its surface on a “long” timescale. This process allows massive dense fragments
to form, which quickly fragment in turn leading to the formation of a cluster
of stars of roughly the same age (Whitworth et al., 1994; Deharveng et al.,
2005). We will therefore concentrate our efforts on testing this specific
triggering mechanism in G305.

In this paper we aim to find out which of the three scenarios mentioned above
is dominant. Based on observations of NH3 inversion lines, Hindson et al.
(2010) found the concentration of star formation tracers in G305 to be
enhanced inside a clump that faces the ionizing sources. The analysis
presented in (Hindson et al., 2010) is consistent with a triggering scenario
but, the evidence is circumstantial. In order to robustly determine which of
the three scenarios presented above dominates, we need to study the
statistical properties of clumps, especially those related to star forming
properties of the clumps, e.g. their masses, luminosity to mass ratios,
surface mass densities. If the feedback is simply moving the clumps around,
there should not be any significant difference in the mass distribution
function of the clumps in G305 when compared to the Galactic average. For the
“dispersion” case we would expect to see fewer clumps and fewer massive
clumps. And finally, if triggering is dominant, we expect to see more massive
clumps when compared to the Galactic average and, in case of an increased star
forming efficiency, a higher luminosity to mass ratio.

We discuss the observations and methods of data reduction in Sec. 2. In Sec.
3, we introduce the ancillary survey data used to aid our analysis. Sec. 4 and
5 explains the details of the clump extraction method and how their properties
were estimated. Sec. 6 explores the effect feedback has on certain clump
properties and how this may support or reject different scenarios presented in
this section. In Sec. 7 we compare the properties of G305 clumps with the
average Galactic sample to provide support for one of the three scenarios.
Finally, Sec. 8 presents the summary of our findings.

##  2 Observations and Data Reduction

The Atacama Pathfinder Experiment (APEX) (Güsten et al., 2006)
telescope111This 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. was used to observe the 1 squared degree region spanning a
longitude range $305\degree<l<306\degree$ and latitude
$-0.5\degree<b<0.5\degree$. The Large APEX sub-Millimeter Array (LAsMA)
receiver (Güsten et al., 2008) was used to observe the $J=3-2$ transitions of
12CO ($\nu_{\text{rest}}\sim 345.796\,$\mathrm{GHz}$$) and 13CO
($\nu_{\text{rest}}\sim 330.588\,$\mathrm{GHz}$$) simultaneously.

The details of the observations, calibrations as well as data reduction has
been described in Paper I. Here we briefly summarize the whole process. The
local oscillator frequency was set at $338.190\text{\,}\mathrm{GHz}$ 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. The whole
region was observed using a position switching on the fly (OTF) technique in
perpendicular directions in order to avoid systematic scanning effects. The
data was calibrated using a three load chopper wheel method, which is an
extension of the “standard” method used for millimeter observations (Ulich &
Haas, 1976) to calibrate the antenna temperature $T^{*}_{A}$ scale. The data
was reduced using the GILDAS package222http://www.iram.fr/IRAMFR/GILDAS.
Baseline subtraction was done on each spectrum after masking the velocity
range $-150\text{\,}\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$ to
$50\text{\,}\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$ in order to avoid fitting
emission features. The average of all the spectra was then used to mask the
channels containing line emissions and baseline fitting was repeated to obtain
a cleaner and flatter baseline. The resulting reduced spectra were then
gridded with a $6$\mathrm{\SIUnitSymbolArcsecond}$$ cell (referred to as a
pixel from now onward) and convolved with a Gaussian kernel with a full width
at half maximum (FWHM) size of one-third the telescope FWHM beam width. The
final datacube has a spatial resolution of
$\sim$20\text{\,}\mathrm{\SIUnitSymbolArcsecond}$$, and a velocity resolution
of $0.5\text{\,}\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$. In order to obtain the
rms noise, the standard deviation was calculated over a range of 100 emission-
free spectral channels for each pixel. Fig. 2 shows the distribution of the
noise in the G305 region for both 12CO and 13CO lines. The noise distribution
peaks at 0.13 K for 12CO and 0.29 K for 13CO . These values were therefore
adopted to be the rms noise (referred to from now as $\sigma_{noise}$) for
each map.

Figure 2: Histogram distribution of rms noise values for the LAsMA map of the
G305 region. The 12CO map’s distribution peaks at 0.13 K and that of 13CO
peaks at 0.29 K as indicated by the blue and red dotted lines respectively.

##  3 Ancillary Data

In order to compare and analyze G305 clump properties with the Galactic
clumps, we have used the clump catalogs from the ATLASGAL (Schuller et al.,
2009; Contreras et al., 2013; Urquhart et al., 2014b) and CHIMPS (Rigby et
al., 2016) surveys. The Galactic clumps derived from the ATLASGAL survey
(Urquhart et al., 2018) have the advantage of having a similar resolution as
the LAsMA data (19$\mathrm{\SIUnitSymbolArcsecond}$). Additionally, there is a
good agreement in the sensitivity between the ATLASGAL data and the ^13CO
intensity map as can be seen in Fig. 3. The sensitivity to column density of
both the data sets are also very similar with LAsMA tracing column densities
down to $\rm{log}(N(H_{2})[\rm{cm}^{-2}]\sim 21.46$ (see Paper I, ) and
ATLASGAL being sensitive to clumps with column densities down to
$\rm{log}(N(H_{2})[\rm{cm}^{-2}]\sim 21.5$ (Schuller et al., 2009; Urquhart et
al., 2018). On the other hand, CHIMPS survey uses the same spectral line
(13CO(3-2)) used in our survey, which makes comparison of properties more
straightforward. But the clumps extraction from CHIMPS survey has been done on
a smoothed dataset of resolution $\sim\,27\,$\mathrm{\SIUnitSymbolArcsecond}$$
(Rigby et al., 2019). Hence, in order to compare the properties of the G305
clumps with the CHIMPS Galactic clumps, we created an additional smoothed
datacube and repeated all the analysis that follows in parallel. While
creating this new dendrogram, a structure was now considered independent only
if it were at least the size of the new beam. All comparison of properties
with the CHIMPS clumps shown in this paper are based on the smoothed datacube.

In order to compare the properties of G305 clumps with any Galactic sample,
similar spatial scales are more important than similar angular resolution.
Therefore, a distance limited sample ($3.5<d<4.5\,\rm{kpc}$) of Galactic
clumps has been used for comparison with clumps in G305. All references to the
Galactic sample of clumps in this paper implicitly imply this distance limited
sample. For the CHIMPS survey it is possible to choose a different range of
distances to avoid smoothing our dataset in order to compare similar clump
sizes. But that leads to fewer clumps in the CHIMPS sample (factor 1.5 fewer
clumps). Therefore, the former method was adopted for comparison with the
CHIMPS sample.

Figure 3: 13CO(3-2) moment-0 map of the G305 region. Overlaid on top are the
contours of ATLASGAL corresponding to intensities 0.6, 1 and 3 Jy/beam.

##  4 Extracting clumps: Dendrogram

Figure 4: Dendrogram of G305 on ^13CO spectral cube. The structures that show
greater than $\sim 67\%$ overlap with the 8 $\mu$m mask (regions with 8 $\mu$m
flux greater than 100 MJy/sr representing molecular gas influenced by feedback
from the central star clusters in G305.) are colored red; those with partial
overlap (between 10 - 67%) are colored green; and the structures with less
than 10% overlap with the 8$\,\mu$m mask are colored blue.

The clump catalog was created using the dendrogram analysis developed by
Rosolowsky et al. (2008). It decomposes the intensity data cube into a nested
hierarchy of structures called leaves, branches and trunks. The leaves are the
highest lying structures (with the brightest intensity) in this hierarchy and
they generally represent the resolution element achievable by the survey
designs. They consist of a collection of isocontours that contain only one
local maximum within them. Branches are the structures that contain other
leaves and branches inside them and trunks are the largest contiguous
structures at the bottom of this hierarchy. Trunks by definition could also be
leaves that are single isolated structures without any parent structure. Hence
each structure identified by astrodendro as either a leaf or a branch
depending on whether it has a lower hierarchy of structures under it.

The dendrogram algorithm astrodendro333astrodendro is a Python package to
compute dendrograms of Astronomical data (http://www.dendrograms.org/). was
run on the data cube in position-position-velocity (ppv) space. A lower limit
($min\\_value$) of 5$\sigma_{noise}$ was set to avoid getting structures with
peak intensity below the noise threshold. Additionally, a structure was
considered independent only if its peak intensity differed by at least
5$\sigma_{noise}$ from the nearest local maximum ($min\\_delta$). Each
structure was required to have an area equal to area of the beam to be
considered real. In the velocity space a minimum width of 4 channels
($=2\,$\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$$) was implemented to prune (get
rid of unwanted structures due to noise in the data) the dendrogram. Figure 4
shows the resulting dendrogram of the 13CO data cube. The branching shows the
fragmentation of a cloud into smaller and denser clumps.

##  5 Catalog of clump properties

Figure 5: Comparison of radii (left), velocity dispersions (center), and masses (right) of leaves and branches in G305.  Table 1: Properties of the 20 randomly selected structures (leaves and branches) derived from the 13CO dendrogram of G305. This table is meant to display a small subset of the whole catalog.aa$a$The full table has been made available electronically. Catalog | Structure | xc | yc | Radius | vrms | log(Lum) | log(Mass) | $\alpha_{\rm{vir}}$ | log($n(H_{2})$) | log($\bar{F}_{8\,\mu m}$)
---|---|---|---|---|---|---|---|---|---|---
Index | Type |  |  |  |  |  |  |  |  |
|  | (∘) | (∘) | ($\mathrm{pc}$) | ($\mathrm{km\,s^{-1}}$) | ($\mathrm{K\,km\,s^{-1}\,pc^{2}}$) | ($\mathrm{M_{\odot}}$) |  | ($\mathrm{cm^{-3}}$) | ($\mathrm{MJy/sr}$)
18 | branch | 305.284 | 0.161 | 13.8 | 4.0 | 3.54 | 5.77 | 0.26 | 2.9 | 2.36
24 | branch | 305.804 | -0.235 | 2.5 | 1.9 | 2.18 | 4.37 | 0.25 | 3.76 | 1.74
28 | branch | 305.222 | 0.119 | 10.7 | 4.5 | 3.3 | 5.54 | 0.43 | 3.0 | 2.39
53 | branch | 305.284 | 0.161 | 13.8 | 4.0 | 3.54 | 5.77 | 0.26 | 2.91 | 2.36
60 | branch | 305.246 | -0.014 | 2.5 | 1.9 | 2.48 | 4.72 | 0.12 | 4.09 | 2.52
67 | leaf | 305.231 | -0.025 | 0.7 | 0.7 | 1.52 | 3.77 | 0.05 | 4.7 | 2.35
84 | branch | 305.865 | -0.045 | 4.2 | 1.4 | 2.43 | 4.54 | 0.17 | 3.21 | 2.02
86 | leaf | 305.612 | 0.143 | 0.8 | 1.8 | 0.99 | 3.69 | 0.35 | 4.58 | 1.8
116 | leaf | 305.175 | 0.254 | 0.5 | 0.9 | 0.01 | 1.66 | 5.67 | 3.21 | 2.15
119 | leaf | 305.223 | 0.324 | 0.6 | 1.0 | 0.54 | 2.68 | 0.82 | 3.95 | 2.06
123 | leaf | 305.928 | -0.1 | 0.3 | 1.2 | 0.05 | 2.02 | 2.35 | 4.33 | 1.7
129 | leaf | 305.208 | 0.141 | 0.6 | 0.7 | 0.72 | 2.88 | 0.31 | 4.09 | 2.1
137 | branch | 305.576 | -0.006 | 4.4 | 2.1 | 2.72 | 4.91 | 0.17 | 3.53 | 2.4
159 | branch | 305.361 | 0.2 | 1.0 | 2.3 | 1.99 | 4.23 | 0.21 | 4.81 | 2.99
187 | branch | 305.564 | 0.002 | 2.3 | 1.8 | 2.42 | 4.61 | 0.12 | 4.09 | 2.53
249 | leaf | 305.67 | 0.025 | 0.6 | 1.5 | 0.71 | 2.74 | 1.62 | 3.95 | 2.29
267 | leaf | 305.552 | -0.055 | 0.7 | 1.2 | 1.16 | 3.47 | 0.23 | 4.49 | 2.29
272 | leaf | 305.681 | 0.307 | 0.9 | 0.9 | 1.14 | 3.65 | 0.13 | 4.3 | 1.91
292 | leaf | 305.493 | 0.01 | 0.3 | 0.8 | -0.28 | 1.84 | 1.71 | 4.11 | 1.82
321 | leaf | 305.28 | -0.153 | 0.6 | 1.0 | 0.32 | 1.86 | 5.77 | 3.1 | 1.76

Once the dendrogram was created, the astrodendro package was used to create a
catalog of some basic properties of all the structures. These include their
positions, mean and RMS velocities, total fluxes and the projections of their
major and minor axes (called $\sigma_{\text{maj}}$ and $\sigma_{\text{min}}$)
on the position-position plane (Rosolowsky & Leroy, 2006). The radius of the
clumps is defined by
$R_{\text{eq}}=\eta*\sqrt{\sigma_{\text{maj}}*\sigma_{\text{min}}}$, where
$\eta$ is a factor that relates the radius of a spherical cloud to its one
dimensional RMS size $\sqrt{\sigma_{\text{maj}}*\sigma_{\text{min}}}$. For
consistency with Solomon et al. (1987); Rosolowsky & Leroy (2006); Colombo et
al. (2019); Rigby et al. (2019) we adopt the value $\eta=1.91$. The velocity
dispersion ($\sigma_{v}$) is calculated as the intensity weighted second
moment of the velocity axis. The flux of the region is the sum (zeroth moment)
of all the emission in the region. The physical radius of the clumps and their
luminosities were calculated using $R_{\text{pc}}=Rd$ and $L=Fd^{2}$
respectively, where $d=3.8\,$\mathrm{k}\mathrm{p}\mathrm{c}$$ is the distance
to G305 (Clark & Porter, 2004; Borissova et al., 2019).

Masses of the clumps were calculated using the column density maps. Sect. 4 of
Paper I describes in detail how the column density map was obtained for the
region. We present a brief summary of the method here. Assuming that ^12CO is
optically thick, the excitation temperature $T_{ex}$ of each pixel in the
position-position-velocity space (referred to from now onward as voxel) was
calculated under the assumption of local thermodynamic equilibrium (LTE).
Then, the ^13CO optical depth was derived for each voxel from the excitation
temperature obtained from 12CO and the 13CO intensity. Subsequently, the ^13CO
column density for each voxel was calculated using the derived excitation
temperature and optical depth. Since, the column density derived is only
available for those pixels with a significant emission in 13CO , all the
properties calculated (and consequently all discussions about the clump
properties) from here on are only applicable to the clumps extracted from the
dendrogram of the 13CO map of the region. As mentioned in Sec. 3 this has the
added advantage of having a similar sensitivity to ATLASGAL data as well as
using the same transition as the CHIMPS survey.

The column density over all the voxels corresponding to each clump in the
dendrogram were added and the mass of the structure was then calculated using
the equation:

$M=\mu\,m_{p}\,R_{13}^{-1}\,\sum_{lmv}N_{13}(\rm{total})_{lbv}\,\Delta x\Delta
y$ (1)

where $\mu$ is the mean mass per H2 molecule, taken to be 2.72, accounting for
a helium fraction of 0.25 (cite Allen 1973), $m_{p}$ is the mass of a proton,
$R_{13}^{-1}$ is the abundance ratio of H2 compared with 13CO, and $\Delta x$
and $\Delta y$ are the resolution element in parsec calculated using the
distance of the source and the resolution element. The conversion
$R_{13}^{-1}$ is calculated in two steps, and we adopt a ratio of
$R_{12}/R_{13}$ that varies as a function of Galactocentric distance as
prescribed by Milam et al. (2005), and a value of $R_{12}=8.5\times 10^{-5}$
(Frerking et al., 1982) is adopted for all sources. $R_{12}/R_{13}$ has a
value of approximately 59.7 for G305’s Galactocentric distance of 6.6
$\mathrm{k}\mathrm{p}\mathrm{c}$.

The masses of the clumps and their radii were also used to calculate their
density($n(H_{2})$) and surface mass densities using:

$\displaystyle n(H_{2})$ $\displaystyle=15.1\times M/(4/3\,\pi
R_{\rm{eq}}^{3})$ (2) $\displaystyle\Sigma$
$\displaystyle=M/\pi\,R_{\rm{eq}}^{2}$ (3)

Here $M$ is in $\mathrm{M}_{\odot}$, $R_{\mathrm{eq}}$ is in
$\mathrm{p}\mathrm{c}$, $n(H_{2})$ is in ${\mathrm{cm}}^{-3}$, and $\Sigma$ is
in $\mathrm{M}_{\odot}\mathrm{/}\mathrm{{}^{2}}{pc}$. The factor of 15.1 is to
convert the density to appropriate units.

The dynamical state of the clumps, i.e. whether they are gravitationally
stable, collapsing or dissipating is examined using the virial theorem. With
only gravitational forces the virial theorem reads $2K+\Omega=0$ where $K$ is
the kinetic energy and $\Omega$ is the gravitational energy. The virial
parameter is defined as the ratio of the virial mass of a spherically
symmetric cloud to its total mass as given below:

$\alpha_{\rm{vir}}=\frac{3\sigma_{\rm{v}}^{2}R_{\rm{eq}}}{GM}.$ (4)

Here, $\sigma_{\rm{v}}$ is the velocity dispersion of the clump and $G$ is the
gravitational constant. This is the definition used by MacLaren et al. (1988).
We also assume a spherical density distribution $\rho(r)=1/r^{2}$. In the
absence of pressure supporting the cloud, $\alpha_{\rm{vir}}<1$ means that the
cloud is gravitationally unstable and collapsing whereas for
$\alpha_{\rm{vir}}>2$ means that the kinetic energy is higher than the
gravitational energy and hence the cloud is dissipating. A value of
$\alpha_{\rm{vir}}$ between 1 and 2 is interpreted to be an approximate
equilibrium between the gravitational and kinetic energies. A cloud undergoing
gravitational collapse can also show $\alpha_{\rm{vir}}\sim 2$ as the rapid
infall can manifest as a large velocity dispersion (Kauffmann et al., 2013).

The dendrogram resulted in a total of 337 structures of which 235 (69.73%) are
leaves, 102 (30.27%) are branches. Fig. 5 shows properties of leaves and
branches to demonstrate their differences. Table $a$ shows 20 randomly
selected clumps in the G305 giant molecular cloud.

##  6 Effect of feedback on G305 clumps

The radiation and ionization front from the OB stars in the central cavity can
effect the masses as well as the velocity dispersion of the clumps in G305. It
can inject turbulence which should manifest as broad linewidths of the clumps.
It can also compress and destabilize the clumps resulting in an increase in
their surface mass densities.

###  6.1 Insufficient velocity resolution

Before we investigate the effects of feedback on the linewidths of clumps we
first calculate whether we posses enough resolution in velocity to discern any
differences that might occur in their linewidths due to feedback. Assuming
that the observed width of a clump is solely attributed to its turbulence, we
can write the turbulent pressure in a clump as,

$P_{\rm{NT}}=n(\ce{H2})m_{\ce{H2}}\sigma^{2}/k\,,$ (5)

where $k$ is the Boltzmann’s constant and $\sigma$ is its velocity dispersion
in one-dimension. If all the turbulent pressure is being delivered to the
clumps by the stars in the center of G305 then $P_{\rm{star}}=P_{\rm{NT}}$,
where $P_{\rm{star}}$ is given by,

$P_{\rm{star}}=Q(H^{0})\langle h\nu\rangle/4\pi d^{2}ck\,,$ (6)

where $Q(H^{0})$ is the number of H ionizing photons per second emitted by the
stars, $\langle h\nu\rangle$ is the mean photon energy of an O-star ($\sim
15$\mathrm{eV}$$ Pellegrini et al. (2007)), $d$ is the distance of the star
(cluster) from the cloud surface, and $c$ is the speed of light. It is tricky
to calculate $P_{\rm{star}}$ given that the distance to each cloud is
different and the stars are also not localized. But in order to obtain an
upper limit on the value of $P_{\rm{star}}$ we assume the total ionizing
radiation of Danks 1 and 2 combined. In Danks 1 we have 2 O8-B3 and 1 O8-B3I
stars for which we adopt the value corresponding to 3 O8V stars from Table 2
of Panagia (1973). Similarly, we use O4V values for the 3 O4-6 stars, O6V
values for the O6-8 and 2 O6-8If stars. For the 3 WNLh stars we adopt the
value corresponding to WN-3w from table 2 of Crowther (2007). Therefore for
Danks 1 we have a maximum ionizing flux equal to $3.67\times
10^{50}\,${\mathrm{s}}^{-1}$.$ For Danks 2, there are 3 O6 (O6-8), 4 O8 (O8-9
/ O8-B3I), and 1 WC7 (WC7-8) stars (we have ignored the F8-G1 star). Assuming
all these belong to class V, we get $8.03\times 10^{49}\,${\mathrm{s}}^{-1}$$.
Hence, Danks 1 and 2 have a combined maximum Lyc photon output of $4.473\times
10^{50}\,${\mathrm{s}}^{-1}$$. The value of $d$ is assumed to be
$4\,$\mathrm{p}\mathrm{c}$$ which is approximately the closest distance of
clumps in the northern and southern complex to the Danks cluster. Plugging
these into Eq. 6, we obtain a value of
$P_{\rm{star}}\sim$1.36\text{\times}{10}^{6}$\,$\mathrm{K}\text{\,}{\mathrm{cm}}^{-3}$$.
This corresponds to a velocity dispersion of
$\sigma=1.06\,$\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$$ given an H2 density of
$10^{4}\,${\mathrm{cm}}^{-3}$$. Since our dataset has a velocity resolution of
0.5 $\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$, it is difficult to discern the
effects of feedback on the velocity dispersion of the clumps, which will
realistically be much smaller than $\sim
1\,$\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$$. The linewidths of the clumps were
plotted as a function of the 8 $\mu$m flux and no dependence was observed
between the linewidths of the clumps at the highest hierarchical level
(leaves) and the strength of the feedback on the clumps supporting our claim.
These results have been presented as an appendix (Fig. 12) as they do not
provide any new information to the question we are trying to answer in this
paper.

###  6.2 Surface mass densities of clumps vs 8 $\mu$m

Figure 6: GLIMPSE $8\,$\mathrm{\SIUnitSymbolMicro m}$$ map of the G305
regions. The black contours correspond to the 13CO J=3–2 integrated
intensities of 5(5$\sigma$), 20(20$\sigma$) and 80 (80$\sigma$)
$\mathrm{K}\text{\,}\mathrm{km}\text{\,}{\mathrm{s}}^{-1}$.

In Paper I we discussed the role of the Galactic Legacy Infrared Mid-Plane
Survey Extraordinaire (GLIMPSE: Benjamin et al., 2003; Churchwell et al.,
2009) 8$\,\mu$m continuum map as an indicator for feedback strength. As a
proxy to the strength of feedback on each clump, we calculated the average
8$\,\mu$m flux over each clump. For this, a mask was extracted for each
structure by projecting it on to the position-position plane and the 8$\,\mu$m
flux was averaged over the mask. Table $a$ also shows the mean 8 $\mu$m flux
associated with each structure.

A significant issue with this analysis is that the 8 $\mu$m map is a 2
dimensional projection on the plane of G305 and hence it is possible for
clumps to appear to be effected by feedback just because of their projection.
In order to test whether the associated 8 $\mu$m fluxes actually correspond to
the clumps we first compared the morphology of the 8 $\mu$m emission with the
13CO integrated intensity map. Fig. 6 shows the GLIMPSE map with the 13CO
integrated intensity contours overlaid on top. There exists very good
correlation between the two. So, we safely assume here that all the 8 $\mu$m
emission is originating in G305. We then investigated whether any leaves in
the dendrogram had the same position but different velocities along the line
of sight. We found only about 1% of the leaves ($\sim 7\%$ if branches are
included) had positions within one beam size distance of another leaf (or
branch). Additionally, Hindson et al. (2013) looked at the morphology of the
molecular gas emission and argued that the G305 complex has a flattened
geometry instead of a spherical structure. Taking these factors into
consideration, one can safely ignore the effects of projection on the
associated 8 $\mu$m fluxes for the clumps.

Figure 7: Surface mass density of clumps in G305 as a function of 8$\mu$m
flux. The orange and blue lines show the results of a power law fit to these
quantities for leaves and branches respectively.

Fig. 7 shows the two-dimensional kernel density estimate (KDE) distribution of
the clump surface mass density as a function of 8$\,\mu$m flux. The leaves and
branches of the dendrogram have been plotted separately. We observe that the
surface mass density of the clumps increase with increasing 8$\,\mu$m flux
indicating that in regions of stronger feedback the clumps are more massive. A
power law fit between the two quantities resulted in the following relation
between them for leaves and branches.

$\displaystyle\Sigma_{l}$ $\displaystyle=56\pm 21\,{\rm{F}}_{8\mu
m}^{\,0.58\pm 0.07}$ (7) $\displaystyle\Sigma_{b}$ $\displaystyle=6\pm
3\,{\rm{F}}_{8\mu m}^{\,1.05\pm 0.09}\,,$ (8)

where $\Sigma_{l}$ and $\Sigma_{b}$ are the surface mass densities of the
leaves and branches respectively, and $\rm{F}_{8\mu m}$ is the average 8$\mu$m
flux incident on the structure. A positive correlation between the surface
mass density of the clumps and the incident 8 $\mu$m flux is indicative of
triggering in G305. In the “redistribution” scenario we would have expected no
correlation between the two quantities and in case of the “disruptive”
scenario one should observe a negative correlation.

###  6.3 Inside and outside the feedback zone

The analysis described in the previous subsection motivated us to follow an
approach similar to that presented in Paper I. Based on an 8 $\mu$m threshold
a “feedback zone” was defined as the pixels with 8$\,\mu$m flux larger than
the threshold. The value of this threshold was chosen to be
$100\,$\mathrm{M}\mathrm{J}\mathrm{y}\mathrm{/}\mathrm{s}\mathrm{r}$$
corresponding to the first inflection point in Fig. 15 of Paper I. We believe
this contour corresponds to the isosurface where the stellar feedback gets
deposited first. Then each clump was assigned a tag depending on the extent of
its overlap with the “feedback zone”. Clumps with more than 67% overlap with
the “feedback zone” were tagged “Mostly Inside”; those with an overlap between
10 and 67% were tagged “Partly Inside”, and those with less than 10% overlap
with the “feedback zone” were tagged “Outside”. This classification is not
based on any physics but in order to aid the explanation that is to follow.
Using this classification results in 95 leaves (40.4%) that were “mostly
inside”, 40 leaves (17.0%) were “partly inside”, and 100 leaves (42.6%) were
“outside” the feedback zone. The same was done with branches which led to 75
branches (73.6%) “mostly inside”, 14 (13.7%) “partly inside”, and 13 (12.7%)
“outside” the feedback zone.

Figure 8: Histogram of the probability density of surface mass densities of
leaves (top) and branches (bottom) based on their overlap with the “feedback
zone” defined using an 8 $\mu$m threshold of
$100\,$\mathrm{M}\mathrm{J}\mathrm{y}\mathrm{/}\mathrm{s}\mathrm{r}$$.

Fig. 8 shows the probability density distribution of the surface mass
densities of the structures based on their tags. There is a clear trend of
increasing surface mass density in association with the overlap with the
feedback zone. A Kolmogorov-Smirnov (KS) test (Kolmogorov, 1933; Smirnov,
1939) was performed on the pairs of these distributions to test the hypothesis
that these samples of surface mass densities have been taken from the same
population. In the case of leaves only the “mostly inside” and the “outside”
samples rejected the null hypothesis (p-value = 0.0011%). The other pair of
samples did not reject the null hypothesis (p-value = 0.12 for “mostly inside”
vs “partly inside” and 0.18 for “partly inside” vs “outside”). But the
branches in the “mostly inside” category were significantly different from
“mostly outside” one (p-value$<<0.0013$) but not from the “partly inside” ones
(p-value=0.002). These findings supports the collect and collapse model that
predicts the clumps to be more massive under feedback.

Another prediction of the C&C model is that there will be a higher level of
fragmentation in the cloud being affected by feedback. To test this, we color
coded the structures of the dendrogram in Fig. 4 based on their tags. We
observe the largest hierarchical structure almost completely lies “mostly
inside” the feedback zone with some structures being “partly inside”. The
structures outside the feedback zone show very little fragmentation. This is
further support for the C&C model in the case of G305.

##  7 G305 vs Galactic clumps

We have seen so far that feedback from the central cluster of stars has a
significant impact on the clumps in G305. This suggests that the properties of
the clumps in G305 should be significantly different from the average sample
of Galactic clumps. In order to test this we compared the properties of G305
clumps with those of the Galactic sample of clumps derived from ATLASGAL and
CHIMPS.

Figure 9: Comparison of properties of LAsMA clumps in G305 with a Galactic
sample derived from ATLASGAL (top panel) and CHIMPS (bottom panel) surveys.
The solid lines overlaid on top in matching colors show the KDE of the
distribution of the corresponding properties.

Fig. 9 shows the distribution of different properties of clumps in G305 along
with the Galactic sample derived for both ATLASGAL clumps (Urquhart et al.,
2018; Contreras et al., 2013) and CHIMPS clumps (Rigby et al., 2019). In order
to compare the clumps properties only the CHIMPS clumps with the highest
reliability flag (= 3) were considered (Rigby et al., 2019).

The radius of the clumps in G305 are smaller than the CHIMPS clumps. This
could be because of the differences in the clump extraction method used by
(Rigby et al., 2019). Compared to the dendrogram clumps, the FELL-WALKER
method (Berry, 2015) would have slightly larger areas. In comparison to
ATLASGAL, the G305 clumps appear to have a different distribution. But this
difference is not significant as confirmed by performing a KS-test on the
radius of the two populations (p-value=0.0022).

The linewidths of the G305 clumps appear to have a different distribution from
the ATLASGAL and CHIMPS samples. A KS-test performed on the linewidths of G305
clumps with the two Galactic samples resulted in a p-value$<<0.0013$ for both
the populations confirming this. The ATLASGAL survey used the NH3 spectral
line to estimate linewidths whereas the CHIMPS survey used the same line used
in our observations and hence this comparison is more straightforward. We
observe the linewidths to be higher in case of G305 clumps when compared to
the CHIMPS population of Galactic clumps.

The G305 clumps show a much broader distribution of masses compared to
ATLASGAL. Higher sensitivity of our observations would explain why we see more
clumps of smaller masses as compared to ATLASGAL as these would not be
detected in the ancillary survey. In comparison to the CHIMPS population of
clumps the masses of G305 clumps are much higher. G305 also has a higher
fraction of heavier clumps compared to the ATLASGAL sample. This is indicative
of some form of triggering. A KS test on the masses of the two populations
resulted in a p-value ¡¡ 0.0013 for masses of G305 clumps as compared to the
Galactic sample (for both ATLASGAL and CHIMPS populations) indicating that the
G305 clumps are significantly different from the Galactic average.

The last panel in Fig. 9 shows the distribution of virial parameters of the
G305 clumps. We see a broader distribution when compared to ATLASGAL clumps. A
large proportion of clumps in G305 appear to have $\alpha_{\rm{vir}}<<2$.
According to Kauffmann et al. (2013) this is indicative of high-mass star
formation in G305. We also see a much higher fraction of clumps in G305 with
$\alpha_{\rm{vir}}>>2$ which may be indicative of turbulence disrupting and
dissipating clumps. Interestingly, the smoothed dendrogram does not have
clumps with very high $\alpha_{\rm{vir}}$ values. This could be attributed to
the bias towards larger structures in the smoothed dataset leading to more
clumps with heavier masses. A KS-test on the virial parameters of the G305 and
Galactic clumps indicated these properties being drawn from significantly
different populations (p-value$<<0.0013$).

### Triggering in G305

Proving that triggering is responsible for enhanced star formation is a
difficult task. Often it is done by looking at the morphological signposts
like star-formation at the rim of an expanding shells of HII regions
(Deharveng et al., 2005; Zavagno et al., 2005; Urquhart et al., 2007; Thompson
et al., 2012; Kendrew et al., 2012; Palmeirim et al., 2017). In G305, Hindson
et al. (2013) looked at star-formation in different phases and compared their
distribution in the complex to suggest that the most likely case of triggering
is the collect and collapse process. However, they did not find any conclusive
evidence that the star-formation happening in G305 has been triggered. They
calculated the time needed for the gas to fragment in to stars and suggested
that while in some cases the age of the triggering stars was old enough to be
responsible for the stars in their vicinity to be triggered. In many other
cases, the stars responsible for triggering may not be old enough to drive the
formation of the HII and UC HII regions. But the fragmentation time-scale
estimates were based on assumptions about the initial ambient atomic density
and the Lyman continuum photon rate both of which are difficult to measure,
making their suggestions inconclusive. So far in this paper, we have explored
whether the feedback from the stars is indeed triggering star formation in
G305 by looking at their impact on the clumps which are the reservoirs of the
new generation of stars.

Figure 10: [Sec.4]: CDF of $L_{clumps}/M_{clumps}$ in G305 compared to that of
the ATLASGAL Galactic clumps.

The luminosity to mass ratio ($L/M$) of clumps is a good indicator of the
evolutionary stage in star formation (see Molinari et al., 2008; Urquhart et
al., 2018). A higher star forming efficiency would mean that more clumps are
in more evolved stages of forming stars leading to a flatter cumulative
distribution function of their $L/M$. In G305, if the clumps are simply being
moved around without any effect on their star forming efficiency, then the
$L/M$ distribution of the clumps in G305 should not vary significantly from
the Galactic average. Fig. 10 shows the cumulative distribution function (CDF)
of the $L/M$ for the ATLASGAL clumps in G305 compared to that of the the
overall ATLASGAL Galactic sample. All the $L/M$ values were taken from
ATLASGAL as the calculation of the luminosity is quite different between our
dataset and ATLASGAL. Consequently, comparing the $L/M$ of clumps from our
data with that of the ATLASGAL clumps would not have been straightforward. The
clumps in G305 show significantly higher $L/M$ than the Galactic average as is
shown by the CDF. A KS test on the two clump samples returned a
p-value$<<0.0013$. Therefore, the null hypothesis is quite overwhelmingly
rejected indicating that the clumps in G305 show higher star forming
efficiency compared to the Galactic average. This rules out the
“redistribution” and “disruption” scenarios. These clumps may not have a one
to one correspondence with the 13CO clumps derived in the previous sections,
but that does not negate the validity of the finding here.

Figure 11: [Sec.4]: CDF of LAsMA clump masses in G305 compared to that of the
Galactic clump sample from ATLASGAL and CHIMPS.

Finally, in case of triggering, if C&C is the dominant mechanism in play then
we would observe more massive clumps as C&C causes the clump to accumulate
mass (Whitworth et al., 1994; Deharveng et al., 2005). Fig. 11 shows the CDF
of the clump masses in G305 compared to the Galactic average. In addition to
the ATLASGAL, we also included the CHIMPS clumps. The method used to measure
clump properties in our paper is identical to that used by Rigby et al.
(2019). Fig. 11 shows the CDF of clump masses in G305 compared to the Galactic
sample taken from ATLASGAL as well as CHIMPS. For both cases the clumps in
G305 show a much flatter CDF than the Galactic average. A KS test between G305
clumps and ATLASGAL (CHIMPS) clumps yielded a p-value$<<0.0013$ again
rejecting the null hypothesis that the G305 LAsMA clumps and the Galactic
ATLASGAL (CHIMPS) clumps belong to the same distribution. The flatter slope of
the clump mass CDF of G305 proves that C&C is the dominant mechanism inside
the GMC.

##  8 Summary

We observed the G305 region with the LAsMA receiver on APEX telescope using
the 12CO ($3\rm{-}2$) and 13CO ($3\rm{-}2$) lines in order to test the effect
of feedback from the central cluster of stars on the clump properties.

We decomposed the molecular cloud into clumps using the Dendrogram analysis on
the 13CO datacube. We followed up by creating a catalog of clump properties
properties. We tested the effect of feedback on two main clump properties
namely linewidths and surface mass densities. Using the 8 $\mu$m emission map
of the region as a proxy to feedback strength, we examined the correlation of
the surface mass densities of the clumps with the incident average 8 $\mu$m
flux. We then mask for the “feedback zone” based on an 8 $\mu$m flux threshold
of 100 MJy/sr. The extent of overlap of each clump with the “feedback zone”
was used to determine whether it was mostly inside, partly inside or outside
the feedback zone. The properties of these three populations of clumps were
separately studied. We followed this up with a comparison of the properties of
clumps in G305 as a whole to a distance limited sample of Galactic clumps
taken from ATLASGAL and CHIMPS surveys assuming that the Galactic sample of
clumps are similar to a population of clumps that are quiescent. The
cumulative distribution function (CDF) of the masses as well as the $L/M$
ratios of the clumps (the latter having been derived entirely from ATLASGAL
data) in G305 was obtained and compared to that of the Galactic average. We
summarize our main findings below :

  * •

Our data does not possess enough velocity resolution to discern the effect of
feedback on the linewidths of the clumps.

  * •

The surface mass densities of the clumps in the region are positively
correlated to the incident average 8 $\mu$m flux.

  * •

The surface mass densities of the clumps mostly inside the feedback zone are
the largest, followed by that of the clumps partly inside and outside the
feedback zone respectively indicating that feedback is triggering their the
star forming ability.

  * •

Clumps inside the feedback zone show much higher level of fragmentation than
those partly inside or outside it.

  * •

The probability density function (PDF) of the properties of G305 clumps are
significantly different than those of the clumps derived from a distance
limited Galactic sample of clumps indicating clear evidences of triggering.

  * •

The CDF of both the masses and $L/M$ ratios of the clumps in G305 are
significantly flatter than that of the Galactic average. This is a strong
evidence for triggering (more specifically the collect and collapse
mechanism), not redistribution or dispersion, being the dominant mechanism in
G305.

Therefore, we obtain multiple evidences demonstrating that the feedback from
the central cluster of stars in G305 is triggering the collapse of the
molecular cloud complex.

###### Acknowledgements.

We thank the staff of the APEX telescope for their assistance in observations.
This work acknowledges support by The Collaborative Research Council 956, sub-
project A6, funded by the Deutsche Forschungsgemeinschaft (DFG). This research
made use of astrodendro, a Python package to compute dendrograms of
Astronomical data (http://www.dendrograms.org/). Data handling in this work
has been done using the Astropy python package (Astropy Collaboration et al.,
2013, 2018). 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.

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##  Appendix A Velocity vs 8 $\mu$m

The linewidths of leaves (highest hierarchical structures) shows no dependence
on the incident 8um flux whereas the branches do show a positive correlation
with the 8 $\mu$m flux. This could be the result of the size versus linewidth
relationship of the clumps. On dividing the linewidths by the size of the
structures (Heyer et al. 2009) the leaves still do not show any strong
dependence of this property on the incident 8 $\mu$m flux. But the branches do
have a weak positive dependence on the incident 8 $\mu$m flux. This indicates
that at larger scales, feedback from the stars does inject turbulence into the
GMC. Similar results were also seen in Paper I where the stacked spectra
showed a positive dependence of their skewness and kurtosis on the incident
8um flux.

Figure 12: Linewidths for G305 clumps as a function of the incident 8 $\mu$m
flux.