# CMZoom IV. Incipient High-Mass Star Formation Throughout the Central
Molecular Zone111©2023, all rights reserved, valid until copyright transferred
to publisher

H Perry Hatchfield Jet Propulsion Laboratory, California Institute of
Technology, 4800 Oak Grove Drive, Pasadena, CA, 91109, USA  University of
Connecticut, Department of Physics, 196A Auditorium Road, Unit 3046, Storrs,
CT 06269 USA  Cara Battersby University of Connecticut, Department of Physics,
196A Auditorium Road, Unit 3046, Storrs, CT 06269 USA  Center for Astrophysics
$|$ Harvard & Smithsonian, MS-78, 60 Garden St., Cambridge, MA 02138 USA
Ashley T. Barnes Argelander-Institut für Astronomie, Universität Bonn, Auf dem
Hügel 71, 53121, Bonn, DE  Natalie Butterfield National Radio Astronomy
Observatory, 520 Edgemont Road, Charlottesville, VA 22903, USA  Adam Ginsburg
University of Florida Department of Astronomy, Bryant Space Science Center,
Gainesville, FL, 32611, USA  Jonathan D. Henshaw Astrophysics Research
Institute, Liverpool John Moores University, 146 Brownlow Hill, Liverpool L3
5RF, UK  Max-Planck-Institute for Astronomy, Koenigstuhl 17, 69117 Heidelberg,
Germany  Steven N. Longmore Astrophysics Research Institute, Liverpool John
Moores University, 146 Brownlow Hill, Liverpool L3 5RF, UK  Cosmic Origins Of
Life (COOL) Research DAO, coolresearch.io  Xing Lu Shanghai Astronomical
Observatory, Chinese Academy of Sciences, 80 Nandan Road, Shanghai 200030,
People’s Republic of China  Brian Svoboda National Radio Astronomy
Observatory, PO Box O, Socorro, NM 87801 USA  Daniel Walker UK ALMA Regional
Centre Node, Jodrell Bank Centre for Astrophysics, The University of
Manchester, Manchester M13 9PL, UK  University of Connecticut, Department of
Physics, 196A Auditorium Road, Unit 3046, Storrs, CT 06269 USA  Daniel
Callanan  Astrophysics Research Institute, Liverpool John Moores University,
146 Brownlow Hill, Liverpool L3 5RF, UK  Center for Astrophysics $|$ Harvard &
Smithsonian, MS-78, 60 Garden St., Cambridge, MA 02138 USA  Elisabeth A. C.
Mills Department of Physics and Astronomy, University of Kansas, 1251 Wescoe
Hall Drive, Lawrence, KS 66045, USA  Luis C. Ho Kavli Institute for Astronomy
and Astrophysics, Peking University, Beijing 100871, China  Department of
Astronomy, School of Physics, Peking University, Beijing 100871, China  Jens
Kauffmann Haystack Observatory, Massachusetts Institute of Technology, 99
Millstone Road, Westford, MA 01886, USA  J. M. Diederik Kruijssen Cosmic
Origins Of Life (COOL) Research DAO, coolresearch.io  Jürgen Ott  National
Radio Astronomy Observatory, 1003 Lopezville Rd., Socorro, NM 87801, USA
Thushara Pillai Boston University Astronomy Department, 725 Commonwealth
Avenue, Boston, MA 02215, USA  Qizhou Zhang Center for Astrophysics $|$
Harvard & Smithsonian, MS-42, 60 Garden St., Cambridge, MA 02138 USA

###### Abstract

In this work, we constrain the star-forming properties of all possible sites
of incipient high-mass star formation in the Milky Way’s Galactic Center. We
identify dense structures using the CMZoom 1.3mm dust continuum catalog of
objects with typical radii of $\sim$0.1pc, and measure their association with
tracers of high-mass star formation. We incorporate compact emission at 8, 21,
24, 25, and 70$\mu$m from MSX, Spitzer, Herschel, and SOFIA, catalogued young
stellar objects, and water and methanol masers to characterize each source. We
find an incipient star formation rate (SFR) for the CMZ of $\sim$0.08 M⊙yr-1
over the next few 105yr. We calculate upper and lower limits on the CMZ’s
incipient SFR of $\sim$0.45 M⊙yr-1 and $\sim$0.05 M⊙yr-1 respectively,
spanning between roughly equal to and several times greater than other
estimates of CMZ’s recent SFR. Despite substantial uncertainties, our results
suggest the incipient SFR in the CMZ may be higher than previously estimated.
We find that the prevalence of star formation tracers does not correlate with
source volume density, but instead $\gtrsim$75% of high-mass star formation is
found in regions above a column density ratio (NSMA/NHerschel) of $\sim$1.5.
Finally, we highlight the detection of “atoll sources”, a reoccurring
morphology of cold dust encircling evolved infrared sources, possibly
representing HII regions in the process of destroying their envelopes.

††software: This research made significant use of Astropy (Collaboration et
al., 2022) This research also utilized astrodendro, a Python package to
compute dendrograms of Astronomical data (http://www.dendrograms.org/) as well
as SAO Image DS9 (Joye & Mandel, 2003), as well as the python module IMF
created by Adam Ginsburg (https://github.com/keflavich/imf).

##  1 Introduction

Understanding how the process of star formation varies with environment
demands the detailed study of molecular cloud evolution under diverse physical
conditions. Star-forming regions in the solar neighborhood provide an
extremely detailed look at the formation of stars in one relatively narrow
window of physical parameter space. The interstellar medium occupying the
radially innermost few hundred parsecs of the Milky Way provides an excellent
opportunity to observe the formation of stars within molecular clouds subject
to a more extreme environment than that of the Galaxy’s disk while still being
nearby enough for modern observatories to resolve the fine details of the star
formation process. The substantial reservoir of gas surrounding the Galactic
Center at a radius of about 100pc known as the Central Molecular Zone (CMZ)
hosts more than 3$\times$107 M⊙ of molecular hydrogen (e.g. Dahmen et al.,
1998; Ferrière et al., 2007), largely contained in giant molecular clouds with
volume densities commonly exceeding 104 cm-3 (e.g. Mills et al., 2018; Guesten
& Downes, 1982), high kinetic temperatures (50-100, e.g. Ginsburg et al.,
2016; Krieger et al., 2017), broad turbulent velocity dispersions ($\sim$10 km
s-1), and complex three-dimensional morphologies (e.g. Shetty et al. 2012;
Henshaw et al. 2016; Kauffmann et al. 2017a; Henshaw et al. 2019). These
conditions bear some resemblance to the properties of z$\sim$1-3 galaxies near
the apex of cosmic star formation, and might be used to further our
understanding of how star formation occurs in the distant reaches of the
universe (e.g. Kruijssen & Longmore, 2013).

Over the last decade, studies measuring the star formation rate (SFR) within
the Galactic Center have revealed a global dearth of recent star formation
relative to the substantial dense gas content (e.g. Immer et al., 2012;
Longmore et al., 2013a; Barnes et al., 2017; Lu et al., 2019a). There are,
however, plentiful signposts of vigorous past and ongoing high and low-mass
star formation throughout the CMZ (e.g. Ginsburg et al., 2018; Walker et al.,
2018, 2021; Lu et al., 2020, 2021). The composition of the Nuclear Stellar
Disk implies periods of much higher SFR within the past $\sim$1 Gyr (Nogueras-
Lara et al., 2020), and the presence of the Arches and Quintuplet star
clusters, thought to have been formed within the last $\sim$6 Myr (e.g. Figer
et al., 2002; Hosek et al., 2019), suggests that the CMZ has a prolific and
irregular star formation history. Some theoretical studies bolster these
claims, showing that computational models of the Milky Way’s CMZ display
highly episodic star formation histories on similar timescales (e.g. Kruijssen
et al., 2014; Krumholz & Kruijssen, 2015; Krumholz et al., 2017; Torrey et
al., 2017; Armillotta et al., 2019; Orr et al., 2021).

There are several young massive clusters (with total masses $\gtrsim
10^{4}$M⊙) actively forming throughout the CMZ, most notably in Sgr B2, Dust
Ridge Clouds C and E, and Sgr C (e.g. Schmiedeke et al., 2016; Ginsburg et
al., 2018; Walker et al., 2016, 2018; Lu et al., 2019a, b; Barnes et al.,
2019; Lu et al., 2021). However, these clouds are only a subset of a
population of massive molecular clouds with extremely high densities, many of
which appear to have few if any signatures of high-mass star formation (e.g.
Longmore et al., 2013a; Lu et al., 2019a; Walker et al., 2021; Williams et
al., 2022). In order to understand the global deficiency of active star
formation in the CMZ relative to its total dense gas mass, we must consider
the complete sample of giant molecular clouds throughout the CMZ.

CMZoom (Battersby et al., 2020) is the first survey at 1.3mm to map all high-
density (N(H${}_{2})>10^{23}$ cm-2) gas in the CMZ with sufficient resolution
and sensitivity to uncover their dense gas substructure on sub-parsec scales.
The survey’s catalog of compact sources, constructed from the Submillimeter
Array (SMA)’s 1.3mm dust continuum emission, characterized all possible sites
of ongoing and incipient high-mass star formation, placing an upper limit on
present-day star formation potential of the Galactic Center (Hatchfield et
al., 2020). However, from the CMZoom’s 1.3mm dust continuum alone, it is
impossible to determine which of these compact submillimeter sources are
actively forming high-mass protostars and which remain quiescent.

In this paper, we perform a detailed analysis of each CMZoom source,
incorporating previous multi-wavelength observations and catalogs of star
formation tracers from the literature to characterize the properties of each
possible site of deeply embedded, incipient high-mass star formation in the
Galactic Center (excluding Sgr A* and Sgr B2). In Section 2, we briefly
summarize the details of the CMZoom survey and describe the design of the
CMZoom catalog. In Section 3, we describe our method for comparing CMZoom
objects with compact far-infrared sources and previous catalogs of young
stellar object (YSO) candidates and masers. In Section 4, we present our
results for which CMZoom clouds host ongoing massive star formation, and how
the physical properties of sources correlate with the indicators of active
star formation. In Section 5, we discuss the implications of these results,
focusing on the scaling relationships and star formation rates presented in
the previous section. Finally, in Section 6, we summarize the results of this
work and list our key conclusions.

##  2 Summary of Data and Catalog Design

The CMZoom survey is an SMA large program, surveying all dense gas
(N(H${}_{2})>$1023 cm-2) in the CMZ. Using the compact and subcompact
configurations of the SMA, the 1.3mm continuum emission achieved a typical
resolution of $\sim$3” ($\sim$0.1pc), revealing a wealth of differing
morphologies and complexities of dust structure in the 35 regions and
$\sim$240 square arcmin ($\sim$1360 pc2) area surveyed. In addition to the
continuum, CMZoom surveyed emission from notable transitions of key molecular
species, such as CO(2-1) and its isotopologue companions, the para-H2CO
triplet transitions ($2_{0,3}-1_{0,2}$, $2_{2,2}-1_{2,1}$, $2_{2,1}-1_{2,0}$),
SiO(5-4) and others, presented in Callanan et al. (2023). While the vast
majority of regions observed by CMZoom have been confirmed to be near the
Galactic Center using a variety of methods including their spectral
properties, a handful of regions (4 of 36) cannot be definitively localized to
the CMZ and may represent foreground emission. These sources (G0.393, G0.212,
G1.670, and G359.137) have been flagged as possible foreground regions, though
they have been included in the following analysis for completeness.

Figure 1: Mosaics of the innermost four degrees of the CMZ constructed from
8$\mu$m (B), 24$\mu$m (G) and 70$\mu$m (R) continuum from GLIMPSE (top,
Benjamin et al., 2003), MIPSGAL (middle, Carey et al., 2009), and Herschel’s
Hi-GAL survey (bottom, Molinari et al., 2010), respectively. Contours in white
are overlaid showing the CMZoom survey footprint in each panel.

The dust continuum catalog, detailed in Hatchfield et al. (2020), was designed
to characterize the properties of the compact dust emission structures
throughout the CMZ’s dense gas content as completely as possible using a
pruned dendrogram. We produce a hierarchical decomposition of the flux
represented by a dendrogram (implemented using
astrodendro222http://www.dendrograms.org/), a tree-like plot where the highest
level, brightest structures are identified as “leaves”. The significance of
each of these leaves is determined by a global estimate of the noise,
$\sigma_{\rm global}$, with a minimum structure boundary value of 3$\sigma$
and a minimum leaf boundary significance of 1$\sigma_{\rm global}$. The
dendrogram algorithm also considers a minimum pixel size for leaves, which we
have chosen to be half the typical beam size. There is no enforced maximum
leaf size, and the shapes and sizes of resulting leaves are entirely
determined by the significance and extent of local maxima in the flux map and
the dendrogram parameters described above. The dynamic range and variable
noise across the surveyed regions necessitated the “pruning” of this initial
dendrogram, in which leaves were removed from the final catalog if they did
not meet a local noise threshold in the mean flux and peak flux. Local root-
means-squared (RMS) noise estimates were constructed from the SMA residual
maps. The only leaves that remain in the catalog are those which have a peak
flux of 6$\sigma$ above the local RMS noise, and a mean flux 2$\sigma$ above
the local RMS. The resulting catalog is uniquely reproducible from the input
dust continuum mosaic and residuals. The interpretation of these leaves is
complicated by their physical scale and the SMA’s physical resolution at the
Galactic Center, as the emission from these leaves is likely due to a
combination of unresolved protostellar sources and resolved dusty envelopes.
ALMA observations of a subset of the CMZoom leaves have revealed a population
of multiple protostellar sources that are unresolved by the SMA, so in this
work we interpret the star-forming sources in the catalog as protoclusters
containing one or more high-mass protostars (e.g. Ginsburg et al., 2018;
Barnes et al., 2019; Walker et al., 2021).

The flux and mass completeness of this catalog were determined using synthetic
interferometric observations of clouds of point-source-like dust sources, and
replicating the imaging pipeline used to process the observed dust continuum
maps of the CMZoom data products. Hatchfield et al. (2020) uses these
synthetic observations to estimate that more than $95\%$ of dust continuum
sources with masses above 80 M⊙ have been recovered by this cataloging
procedure and are characterized in the high robustness version of the CMZoom
catalog (assuming an average dust temperature of at least 20K across the
entire dendrogram leaf). Using this mass completeness, given an initial mass
function (IMF, e.g. Kroupa 2001) and an assumed star formation efficiency
(SFE) for star-forming structures on scales resolved by the SMA, this mass
completeness limit suggests that virtually all (more than 95$\%$ for ) of
possible sites of deeply embedded high-mass star formation within the CMZ are
included within the CMZoom catalog. While the CMZoom survey does not observe
the entire contiguous spatial range of the CMZ, it does sample all regions
above a column density of 1023 N(H2) cm2, and therefore is almost certain to
capture the deeply embedded high-mass star formation present in this extreme
part of the Galaxy (Battersby et al., 2020). It must also be noted that the
catalog does not include star-forming sources that are sufficiently evolved to
destroy their envelopes, though such sources account for a large portion of
the star formation tracers throughout the CMZ considered in the other work
cited throughout. The present analysis aims to characterize an earlier stage
of star formation, during which the young protosclusters are still embedded in
their cold envelopes.

##  3 Method

###  3.1 Selection and Identification of Star Formation Tracers

By comparing positions and properties of CMZoom catalog leaves with the
positions of a variety of previously catalogued tracers of active or recent
star formation, we determine the incipient star formation rate for each source
in the CMZoom Survey. The presence of certain maser species are known to trace
recent star formation within molecular clouds. In particular, emission at 6.7
GHz from methanol (CH3OH) masers indicates ongoing high-mass (M $>$ 8M⊙) star
formation (e.g. Minier et al., 2003; Xu et al., 2008). Water (H2O) masers are
commonly associated with both high and low-mass star-forming regions, but may
also indicate the presence of evolved sources on the asymptotic branch of AGB
stars, Mira variables, and possibly other astrophysical phenomena (e.g. Hinkle
& Barnes, 1979; Forster & Caswell, 1999; Miranda et al., 2001), but such
sources will be much dimmer and can be excluded based on their emission in
other wavebands (Longmore et al., 2013b). We consider the coincidence of
methanol or H2O masers with CMZoom catalog objects as an indication that those
leaves are actively forming high-mass stars. We incorporate the 6.67 GHz
emission from CH3OH masers catalogued using the Parkes telescope by Caswell et
al. 2010 and the J=61,6-52,3 transition of H2O masers catalogued using the
Australia Telescope Compact Array (ATCA) by Walsh et al. 2014. If a CMZoom
catalog leaf’s contour overlaps with one of the masers from either of these
catalogs within the reported astrometric uncertainty (see Table 1), it is
considered associated and the leaf is considered to have a robust signature of
active star formation. While deeper and higher resolution maser observations
are available for a subset of the CMZoom area (e.g. Lu et al., 2015, 2019a),
we do not include the analysis of these data here in order to preserve a
consistent approach across all regions in the survey.

We must consider that these masers may not be present or detectable at all
sites and evolutionary stages of incipient star formation, so we also consider
the presence of mid and far-infrared continuum emission from the dusty
envelopes of young protoclusters. The presence of point-like far-infrared
emission between 20 and 70$\mu$m associated with a compact submillimeter dust
source is a signature of early high-mass star formation (e.g. Yusef-Zadeh et
al., 2008), since the spectral energy distributions (SEDs) of dust surrounding
Class 0 and I protostars peak in the far-infrared. While some populations of
evolved stars may display similar far-infrared profiles, potentially
masquerading as high-mass YSOs, these compact far-infrared sources that are
associated with cold, dense submillimeter gas structures are much less likely
to be interlopers (e.g. Schultheis et al., 2003; An et al., 2011; Koepferl et
al., 2015).

Past surveys have catalogued point-like infrared sources according to a
variety of other criteria, identifying a large number of YSO candidates
throughout the Galactic Center. Here, we cross-correlate the locations of
24µmand 70µmpoint-like sources identified by Gutermuth & Heyer (2015) and
Molinari et al. (2016), respectively. The 24µmpoint source catalog presented
by Gutermuth & Heyer (2015) using data from the MIPSGAL Survey (Carey et al.,
2009) is constructed using PhotVis, a modification of the DAOFIND algorithm
(Gutermuth et al., 2008; Stetson, 1987). CMZoom sources with a leaf contour
overlapping within one MIPSGAL beam (as used in generating the catalog, 6.25”
FWHM) are considered associated with the YSO candidate and thus are considered
robustly star-forming. The 70µmpoint source catalog generated from the Hi-Gal
survey (Molinari et al., 2010, 2016) is generated using the CuTex algorithm,
which fits 2D Gaussians to perform photometry by considering the curvature of
the flux map (Molinari et al., 2011). Any CMZoom sources whose leaf contour
overlaps within one Hi-Gal beam FWHM ($\sim$5”) of these sources are
considered as associated.

We perform the same general procedure for several previous catalogs of YSO
candidates throughout the survey region. An et al. (2011) identify YSO
candidates from the infrared point source catalog presented in Ramírez et al.
(2008) using spectra from 5-35$\mu$m from the Infrared Spectrograph (IRS) of
the Spitzer space telescope. Yusef-Zadeh et al. (2009) use 24 and 70$\mu$m
observations with Spitzer/MIPS, supplemented by other far-IR, submillimeter
and radio observations to identify a large sample of YSOs in the Galactic
Center, though this sample is likely contaminated with a significant fraction
of evolved stars interacting with surrounding dust (Koepferl et al., 2015).
Lastly, we consider the YSO catalog produced by Immer et al. (2012) by
analyzing SEDS observed with IRS toward point sources identified using ISOGAL
(Schuller et al., 2003; Omont et al., 2003). For each of these previous YSO
catalogs, we determine their association with the CMZoom sources using the
beam FWHM from the corresponding instruments as the corresponding astrometric
uncertainty. Leaves with contours overlapping within the positional
uncertainty of these YSOs are flagged as “robustly star-forming”.

Figure 2: An example (Sgr C) of the three-color images used in the by-eye
search for compact emission signifying the early onset of star formation
associated with CMZoom catalog objects. The three colors used in the top panel
are 8$\mu$m (blue, GLIMPSE, from Benjamin et al. (2003), 24$\mu$m (green,
MIPSGAL, from Carey et al. 2009), and 70$\mu$m (red, Hi-Gal, from Molinari et
al. (2010)). These are each shown individually in the bottom four panels,
along with the 21$\mu$m emission from MSX (Egan et al., 2003). Overlaid on the
composite three-color image are white contours outlining the CMZoom leaves,
along with cyan circles demarcating YSO candidates from a compilation of those
identified by Yusef-Zadeh et al. (2009), An et al. (2011), and Immer et al.
(2012), purple circles indicating the 70$\mu$m point sources catalogued by
Molinari et al. (2010), and darker blue circles representing the point sources
identified by Gutermuth & Heyer (2015). The radial size of these circles
corresponds to the FWHM condition used do determine plausible association with
CMZoom leaves. The bottom panel shows a 70$\mu$m mosaic of the Galactic Center
with each CMZoom region shown as black box, with the specific region from the
above panels highlighted in red. In this case, leaves a, b, and c are labeled
have robust signatures of high-mass star formation, and have been flagged as
“robustly star-forming” in the catalog, while leaves d and e are labeled
“robustly quiescent”. The full sample of clouds is presented in Appendix A.

###  3.2 Cataloging of Compact Far-Infrared Sources By-Eye

To supplement the previously noted sources in the far IR, we performed a by-
eye search for point-like emission in the 8$\mu$m, 21$\mu$m, 24$\mu$m and
70$\mu$m dust continuum associated with each CMZoom robust catalog source.
This combination of determining association with star formation tracers
algorithmically as well as by-eye is helpful because the far-IR dust continuum
landscape of the Galactic Center is very complex, with highly variable
background levels and noise properties, significant potential for confusion
with foreground sources, and bright extended emission that is not necessarily
associated with sites of early star formation. Performing a by-eye survey
allows us to handle ambiguous cases that may have been missed or
mischaracterized in previous studies on an individual basis while using
independent selection criteria.

Figure 3: A comparison of the MIPSGAL (top panel) and SOFIA FORCAST (bottom
panel) observations toward a subset of CMZoom fields near the Galactic
Nucleus, including “The Three Little Pigs” and “The 50 km s-1 Cloud”. The
saturated regions in MIPSGAL are resolved with FORCAST, though the FORCAST
Galactic Center Survey does not cover all regions observed by CMZoom, and so
could not be applied to the entire catalog sample.

The goal of this search was to robustly identify the presence or absence of
any signature of active high-mass star formation. To further mitigate the
inherent biases of human error in performing this by-eye cataloging, eight
team members (initials HH, CB, AB, NB, SL, XL, BS, DW) performed the task
independently. Each team member, using locally-scaled RGB maps (R: 70$\mu$m,
G: 21$\mu$m and 24$\mu$m and B: 8$\mu$m, e.g. Fig 2), designated either a
“robust detection”, “robust non-detection”, or “ambiguous detection” for each
star formation tracer, for each of the 285 high-robustness catalog sources. A
final determination of “robustly star-forming”, “robustly-non-starforming”
(or, equivalently, “robustly quiescent”, and “ambiguous star-forming state”
was then decided considering the compilation of the independent results.
Leaves with significant consensus (at least 6 of the 7 team members in
agreement) for a certain designation for 70$\mu$m, 21$\mu$m or 24$\mu$m point-
like sources were considered to be robustly star-forming or robustly
quiescent, corresponding to the consensus. Leaves for which significant
disagreement was recorded ($\geq 2$ disagreeing designations) were re-
inspected to determine if there was a discernible cause for the discrepancy,
or if the leaf should be designated as “ambiguous”. The most prevalent cases
for ambiguity are marginally compact sources embedded in or near bright,
structured extended emission. While it is possible that these ambiguous
sources are actively star-forming, their properties cannot be easily
distinguished from their envelope emission, and higher resolution and
sensitivity measurements or more sophisticated fitting techniques (e.g. Immer
et al., 2012) would be necessary to arrive at a more definitive designation.
Therefore, such leaves are designated as “ambiguously star-forming” in the
following analysis.

###  3.3 Sources of Uncertainty in the By-Eye Analysis

In identifying the association of each high-mass star formation tracer with
the catalog leaves, there are several opportunities for ambiguity and
uncertainty that must be addressed. While the majority of sources designated
as “robustly star-forming” or “robustly quiescent” had near-unanimous
agreement about the presence or absence of each star formation tracer,
ambiguous edge-cases were re-inspected by eye by only one team member,
compiling the previous results and reaching a final designation based on the
relevant context. It is clear that this final designation for the cases
handled in this way might be biased, but such edge-cases largely fell into two
categories. Firstly, for regions with bright but diffuse emission suffusing
the leaf contours and their immediate surroundings with non-point-source-like
substructure, some team members marked leaves as having compact far-IR
emission. Secondly, some leaf contours overlap with, but are not centered on a
bright, far-IR compact source, and some team members marked such leaves as
non-star-forming. The final designation for leaves in both cases was
“ambiguously star-forming” unless other information was available to better
constrain their properties.

The by-eye component of the star formation tracer cataloging does not
significantly alter the statistics of the final populations. Only 11 CMZoom
leaves achieved a “robustly star-forming” designation without association with
a previously-catalogued star formation tracer, of which 10 are in the
immediate proximity, though not overlapping with, a previously-catalogued
tracer. The remaining source, G0.619+0.012i, hosts a clear 8$\mu$m point
source and a much more subtle 24-25$\mu$m point source, visible in both
MIPSGAL and SOFIA FORCAST continuum observations. Because of the low signal-
to-noise value for this far-IR source, it is possible previous automatic
cataloging algorithms have missed it, and the presence of a cold 1.3mm
continuum envelope better highlights its likely-protostellar nature. While
many of the more “ambiguously star-forming” sources may correspond to
previously not-catalogued YSO candidates, characterizing their nature is left
for future efforts using a more complete set of observations.

###  3.4 Accounting for Saturated Pixels with SOFIA FORCAST Data

Several regions in the CMZoom field are saturated in the 24µmemission map from
Spitzer/MIPS (see section 5.2 in Carey et al. (2009)). Because these saturated
sources in the MIPSGAL field are typically associated with compact, bright
far-infrared sources, some are particularly relevant to the present study. We
consider lower resolution 21µmmaps from MSX (Egan et al., 2003) in cases of
saturation in the MIPSGAL maps. In the most complex regions of the CMZ’s warm
dust component, the additional spatial resolution gained by considering more
recent observations from other instruments is critical for distinguishing the
star-forming properties of the relevant CMZoom catalog objects.

To that end, we use data from the FORCAST Galactic Center Legacy Survey
(Hankins et al., 2019, 2020) to characterize the compact 25.3µmemission
associated with the 34 CMZoom catalog objects for which Spitzer/MIPS data are
saturated. An example of such a region is shown in Figure 3. Using these data,
we confirm whether the CMZoom sources host signatures of high-mass star
formation. Several key CMZoom clouds are not covered by the SOFIA FORCAST
Galactic Center Survey (most notably the 1.6 degree cloud complex, the 50 km
s-1 cloud, and the Dust Ridge clouds), so this analysis is not available for
all leaves in the catalog. This may lead to a potential bias in the identified
star-forming sources, as it is possible that higher-resolution measurements
with greater sensitivity to far-infrared point-sources from SOFIA’s FORCAST
instrument or future observatories would reveal even more compact emission
within seemingly quiescent CMZoom catalog leaves. Future analysis will be
expanded to include a more detailed characterization of the CMZoom sources
using the data available from the FORCAST Galactic Center Legacy Survey.

###  3.5 Summary of Method for Star Formation Designation

For the sake of clarity, here we concisely summarize the procedure for
identifying which of the CMZoom sources are “robustly star-forming”, “robustly
quiescent”, and “ambiguously star-forming”. A source is considered “robustly
star-forming” if it has:

  * •

A previously identified YSO within its leaf contour, within the uncertainty of
the YSO’s position

  * •

A previously catalogued H2O or CH3OH maser within its leaf contour, up to the
maser’s positional uncertainty

  * •

A previously catalogued 24$\mu$m or 70$\mu$m point source overlapping the leaf
contour, within the beam of the corresponding observation

  * •

A by-eye determined point-like source of 21$\mu$m, 24$\mu$m, 25$\mu$m, or
70$\mu$m emission overlapping with the leaf contour.

A source is designated as “robustly quiescent” if it has none of the above
signatures of high-mass star formation. Finally, a source is considered
“ambiguously star-forming” if any of the above criteria are ambiguously valid,
or if the by-eye designation was clouded by bright and diffuse emission
surrounding the source.

##  4 Results

###  4.1 The Star-Forming Properties of CMZoom Sources

The expansion of the cmzoom catalog produced via the methods described in the
previous section has been made available online on the CMZoom dataverse, along
with the rest of the survey’s data
products333https://dataverse.harvard.edu/dataverse/cmzoom. With this compiled
catalog of deeply embedded star formation throughout the CMZ, we can consider
the physical properties of the CMZoom leaves in the context of their star-
forming status. The properties we consider here are those reported in the
CMZoom survey’s high-robustness catalog444This catalog is on the CMZoom
Dataverse at https://doi.org/10.7910/DVN/RDE1CH (catalog DOI:
10.7910/DVN/RDE1CH), and their calculation is fully explained in Hatchfield et
al. (2020), though we briefly review several key definitions here.

Table 1: A brief summary of which data are used as tracers of incipient and ongoing star formation in this work.  Star Formation Tracer | Astrometic Uncertainty | Citation
---|---|---
8$\mu$m point-like emission | – | Benjamin et al. (2003)
21$\mu$m point-like emission | – | Egan et al. (2003)
24$\mu$m point-like emission | – | Carey et al. (2009)
70$\mu$m point-like emission | – | Molinari et al. (2010, 2011)
Prev. catalogued 70$\mu$m point sources | 5” | Molinari et al. (2016)
Prev. catalogued 24$\mu$m point sources | 6” | Gutermuth & Heyer (2015)
H2O Masers (J = 61,6 \- 5 2,3) | 1” | Walsh et al. (2014)
CH3OH Masers (6.7GHz) | 0.6” | Caswell et al. (2010)
Prev. catalogued YSOs | 2-6” | An et al. (2011); Immer et al. (2012)

The compact dust sources resolved by CMZoom are defined as the leaves of the
dendrogram produced by the astrodendro algorithm applied to the entire survey
mosaic, and do not necessarily display elliptical boundary contours. We
consider the effective radius of each source to be $R_{\rm eff}\equiv(N_{\rm
pix}A_{\rm pix}/\pi)^{1/2}$, with $N_{\rm pix}$ as the number of pixels
associated with a given dendrogram leaf and $A_{\rm pix}$ being the area of a
single pixel. The mass of each catalog source is defined as

$M_{\rm leaf}=\frac{d^{2}S_{\nu}R_{\rm gd}}{\kappa_{\nu}B_{\nu}(T_{\rm d})},$
(1)

where $d$ is the distance to the Galactic Center (8.2kpc, Collaboration,
2019), $S_{\nu}$ is the leaf’s integrated flux, $R_{\rm gd}$ is the gas-to-
dust ratio (taken to be 100, e.g. Battersby et al. 2011), $\kappa_{\nu}$ is
the dust opacity at frequency $\nu$ and $B_{\nu}(T_{\rm d})$ is the Planck
function evaluated for dust temperature $T_{\rm d}$, as determined from
Herschel dust emission modeling (Mills & Battersby 2017). We also derive
source-scale column densities from the CMZoom data, calculated for each
catalog leaf as

$N_{\rm H_{2}}=\frac{F^{\rm peak}_{\rm\nu}R_{\rm gd}}{\mu_{\rm H_{2}}m_{\rm
H}\kappa_{\nu}B_{\rm\nu}(T_{\rm d})},$ (2)

using the same definitions as above, with $F^{\rm peak}_{\rm\nu}$ as the
leaf’s peak flux density in Jy beam-1, $\mu_{\rm H_{2}}$ as the mean atomic
weight (2.8, e.g. Kauffmann et al. 2008), and $m_{H}$ as the mass of hydrogen.

Using the total leaf mass $M_{\rm leaf}$ defined above in equation 1, we can
estimate the average number density of each leaf by assuming that each leaf’s
mass is distributed uniformly with spherical symmetry inside a radius equal to
$R_{\rm eff}$. This simplifying assumption yields

$n(H_{2})=\frac{3M}{4\pi R_{\rm eq}^{3}\mu_{\rm H_{2}}m_{\rm H}}.$ (3)

from which we can also construct the object’s free-fall time,

$t_{\rm ff}=\bigg{(}\frac{3\pi}{32G\mu_{\rm H_{2}}m_{\rm H}n_{\rm
H_{2}}}\bigg{)}^{1/2},$ (4)

where $G$ is the gravitational constant and the remaining variables and
constants are the same as defined above. The cloud-scale column density used
in the following analysis is similarly derived from modeling the spectral
energy distribution of dust measured by Herschel, which will be presented in
Battersby et al. in prep. The spatial resolution of this Herschel-derived
column density is 36”, or about 1.4pc at the distance of the Galactic Center.

In Figures 4 and 5, we consider how the fraction of leaves with indications of
active star formation correlates with the catalog properties. For this
analysis, we exclude the regions surrounding Sgr B2 and Sgr A∗. We exclude the
former since the region hosts a particularly massive, more-evolved
protocluster for which significantly more accurate estimates of star formation
rates and high-resolution YSO counting and modeling are available (for
example, see Schmiedeke et al. 2016 and Ginsburg et al. 2018). We exclude the
region surrounding Sagittarius A and the circumnuclear disk due to the highly
non-Gaussian noise and contamination from synchrotron emission described in
more detail in Battersby et al. 2020. Excluding these regions, we find a total
of 39 leaves with a robust signature of active star formation, 57 leaves with
ambiguous signs of active star formation, and 104 leaves with a robust non-
detection of active star formation. These results are displayed for only
robustly star-forming sources in Table 2 and for robustly and ambiguously
star-forming sources in Table 3.

Figure 4:  The physical properties of the robustly star-forming CMZoom catalog
objects compared with the properties of all catalog objects (from left to
right: volume number density of H2, total leaf mass, peak column density of H2
resolved by the SMA, and the cloud-scale column density in H2 as measured by
Herschel). Each bottom panel shows a binning of the CMZoom catalog’s
distribution for the respective property. Each panel shows three histograms,
the dark purple histogram shows the distribution of leaves associated with
robust tracers of active star formation, the pale purple histogram shows the
distribution of leaves with either robust or ambiguous star formation
signatures, and the distribution of all leaves is shown in light blue. The
solid black line in the upper panels for each physical property shows the
ratio between the histogram counts for the distributions of star-forming
leaves for each bin, representing the fraction of leaves at that quantity’s
value that are robustly forming stars. A region is shown above each of these
representing how this fraction increases if we include the ambiguous star
formation tracers as well. Figure 5: A continuation of Figure 4. The physical
properties of the robustly star-forming CMZoom catalog objects compared with
the properties of all catalog objects (from left to right: the column density
ratio (NSMA / NHerschel), the leaf free-fall time, the local dust temperature,
and the leaf effective radius). Each bottom panel shows a binning of the
CMZoom catalog’s distribution in the respective physical properties. Each
panel shows three histograms, the dark purple histogram shows the distribution
of leaves associated with robust tracers of active star formation, the pale
purple histogram shows the distribution of leaves with either robust or
ambiguous star formation signatures, and the distribution of all leaves is
shown in light blue. The solid black line in the upper panels for each
physical property shows the ratio between the histogram counts for the
distributions of star-forming leaves for each bin, representing the fraction
of leaves at that quantity’s value that are robustly forming stars. A region
is shown above each of these representing how this fraction increases if we
include the ambiguous star formation tracers as well.

###  4.2 Star Formation Rates of CMZ clouds

With a robust estimate of the star formation status of the CMZoom catalog
sources, we can derive a new estimate for the SFR of each cloud observed by
CMZoom. Hatchfield et al. 2020 calculated an upper limit on the SFR of the
CMZ, a star formation potential, in the range of 0.08 - 2.20 M⊙ yr-1 (or 0.04
- 0.47 M⊙ yr-1 excluding Sgr B2) depending on the assumed star formation
efficiency. This method makes the assumption that each of the catalogued
objects will collapse to form stars on their free-fall timescales, which is
likely to overestimate the resulting star formation rates. By considering
which of these sources are associated with active star formation tracers, we
can provide a more accurate estimate of the incipient star formation rate of
clouds in the CMZ.

To calculate the incipient star formation rates for the CMZoom clouds, we
follow a modified version of the procedure used in Hatchfield et al. 2020 for
each catalog leaf with a robust star formation tracer. We translate the
properties from the catalog into star formation rates for each of the CMZoom
clouds as the summation of the individual leaves’ star formation rates, using

$\text{SFR}_{\rm cloud}=\frac{\epsilon_{\rm SF}}{\xi_{\rm
IMF}}\sum_{i}\frac{M_{i}}{t_{ff,i}},$ (5)

where the sum runs over the $i$ leaves in the cloud, $M_{i}$ and $t_{ff,i}$
are respectively the mass and free-fall time of the $i$th star-forming leaf,
$\epsilon_{\rm SF}$ is the star formation efficiency per freefall time, and
$\xi_{\rm IMF}$ is a correction to account for low-mass star formation to
which the CMZoom catalog and the tracers used in this work are not sensitive.
In this equation, we make several simplifying assumptions. Firstly, we must
choose an average star formation efficiency with which these structures are to
form stars over the course of a free-fall time. We assume that each leaf is
forming stars with an efficiency

$\epsilon_{\rm SF}=0.25\pm 0.15$ (6)

over the course of one of the leaf’s free-fall time, $t_{ff}$. The star
formation efficiency per free-fall time has been investigated on the scales of
individual protostellar cores ($\sim 20-50\%$, e.g. Walker et al. (2018);
Barnes et al. (2019)) as well as on cloud scales ($\sim$1-10%, e.g. Leroy et
al. (2017); Barnes et al. (2017); Utomo et al. (2018); Krumholz et al. (2019);
Lu et al. (2019b); Grudić et al. (2022); Chevance et al. (2022)), but on the
intermediate scales investigated in this work, it is unclear what a realistic
value might be. The range of values assumed above is intended to be broad
enough to encompass a variety of sensible possibilities in agreement with the
values estimated for bounding physical scales.

The high-mass star-forming sources characterized here only provide a partially
complete picture of the CMZ’s incipient star formation. There is substantial
evidence for a lower-mass star-forming population in both the most prolific
clouds, such as Sgr B2 (Ginsburg et al., 2018) as well as the supposedly most
star formation-deficient clouds, like The Brick (Walker et al., 2021). These
lower mass protostellar populations are not likely to be detectable using the
method employed in this work. While the CMZoom catalog is complete to more
than 95% of all possible sites of incipient high-mass star formation (the
robust catalog is complete to $>95\%$ of sources with total gas mass $>80$M⊙
for an assumed dust temperature $>$20K, Hatchfield et al. (2020)), it is not
sensitive to the population of more isolated low-mass protostars that have
been detected in some of the Galactic Center’s molecular clouds.

To account for the missing star-forming mass associated with the lower-mass
star protostellar objects in the CMZ, we extrapolate from the stellar Initial
Mass Function, or IMF (Kroupa, 2001) using the IMF python module
(https://github.com/keflavich/imf). By drawing 1000 samples from the IMF of a
cluster with a mass of $>100$ M⊙ (sufficiently above the CMZoom catalogs’
completeness), we find that an average of $\xi_{\rm IMF}\approx 20\%$ of the
cluster’s star mass is ultimately contained in high-mass protostars555The
high-mass stars’ contribution to the total fraction of star mass in a cluster
is approximately the same for clusters with mass above 100M⊙, but may be
smaller for low-mass clusters for which the high mass tail of the IMF is not
well sampled.. This may be an overestimate for sources that contain
significant further fragmentation that includes a significant number of lower-
mass protostars, but if the flux detected with the SMA is largely due to dust
associated with gas around high-mass protostars, then it is not likely to be a
significant overestimate. Future observations capable of measuring the masses
of a more complete sample of the CMZ’s protostellar population are necessary
to better approximate this value.

The uncertainties for these values are dominated by our assumptions in
$\epsilon_{\rm SF}$, $\xi_{\rm IMF}$, as well as the systematic uncertainties
in our assumed value of the gas-to-dust ratio, dust grain properties and the
random uncertainty from noise in the SMA’s flux measurements. The
uncertainties in mass, dust temperature, and free-fall time are further
detailed in Hatchfield et al. 2020. The masses reported in the catalog use
dust temperatures calculated from Herschel SED fitting (Battersby et al. in
prep.), and therefore apply to a spatial scale of 36”, significantly larger
than the size of the CMZoom catalog objects. It is likely that dust
temperatures would be systematically higher for sites of active star formation
on smaller spatial scales, so the star formation rates calculated using the
Herschel temperatures may be too high. This is because an assumed lower
temperature in Equation 1 implies a higher mass (and similarly a shorter
freefall time from Equations 3 and 4), leading to a significantly elevated SFR
using Equation 5. Dust temperatures on the scales of individual cores in the
CMZ may be higher, $57-220$K or greater (Walker et al., 2018), so we expect
the temperatures on the intermediate scales probed by CMZoom to be
respectively intermediate to the Herschel-derived values and the core
temperatures, though where they fall between these boundary values is
difficult to constrain further without higher resolution observations in far-
infrared and submillimeter bands. The values of the star formation rates for
each cloud are reported in Table 2 assuming both the Herschel-derived
temperatures and an intermediate dust temperature of 50K.

Table 2: The summary of the star-forming properties for each cloud in the CMZ considering only robustly star-forming sources. The first three columns include a coordinate name, colloquial name and cloud mask index for each cloud. The column “SFRHerschel” represents the star formation rate calculated in equation 5, assuming a dust temperature from Herschel, as reported in the catalog, with uncertainties due to star formation efficiency and random error in the mass estimation. The column “SFR50K” represents the star formation rate calculated in equation 5, assuming a dust temperature of 50K, with uncertainties due to star formation efficiency and random error in the mass estimation.The column “NSF” lists the number of robustly star-forming sources within each CMZoom cloud and the final column NSF/Ntot lists the fraction of sources with robust star formation tracers in each cloud. For clouds without star formation tracers, and for Sgr B2, these numbers are omitted and replaced with a dash.  Cloud ID | Colloquial Name | CMZoom | SFRHerschel | SFR50K | NSF | NSF/Ntot
---|---|---|---|---|---|---
|  | mask number | 10-3 M⊙yr-1 | 10-3 M⊙yr-1 |  |
G1.683-0.089 |  | 1 | – | – | 0 | –
G1.670-0.130 |  | 2 | 3.2$\pm$1.9 | 0.4$\pm$0.2 | 2 | 0.33
G1.651-0.050 |  | 3 | 1.5$\pm$0.9 | 0.2$\pm$0.1 | 1 | 0.50
G1.602+0.018 |  | 4 | 4.0$\pm$2.4 | 0.4$\pm$0.3 | 1 | 0.20
G1.085-0.027 |  | 5 | 6.5$\pm$3.9 | 1.0$\pm$0.6 | 2 | 0.67
G1.038-0.074 |  | 6 | – | – | 0 | –
G0.891-0.048 |  | 7 | – | – | 0 | –
G0.714-0.100 |  | 8 | – | – | 0 | –
G0.699-0.028 | Sgr B2 | 9 | – | – | 0 | –
G0.619+0.012 | Sgr B2 SE | 10 | 30.0$\pm$18.0 | 8.1$\pm$4.9 | 7 | 0.70
G0.489+0.010 | Dust Ridge Clouds E&F | 11 | 15.9$\pm$9.5 | 2.8$\pm$1.7 | 1 | 0.08
G0.412+0.052 | Dust Ridge Cloud D | 12 | – | – | 0 | –
G0.393-0.034 |  | 13 | – | – | 0 | –
G0.380+0.050 | Dust Ridge Cloud C | 14 | 37.9$\pm$22.8 | 10.0$\pm$6.0 | 1 | 0.12
G0.340+0.055 | Dust Ridge Cloud B | 15 | – | – | 0 | –
G0.326-0.085 | The Sailfish | 16 | – | – | 0 | –
G0.316-0.201 |  | 17 | – | – | 0 | –
G0.253+0.016 | The Brick | 18 | – | – | 0 | –
G0.212-0.001 |  | 19 | 5.0$\pm$3.0 | 1.6$\pm$0.9 | 3 | 0.60
G0.145-0.086 | The Straw Cloud | 20 | – | – | 0 | –
G0.106-0.082 | The Sticks Cloud | 21 | – | – | 0 | –
G0.070-0.035 |  | 22 | – | – | 0 | –
G0.068-0.075 | The Stone Cloud | 23 | 2.2$\pm$1.3 | 0.6$\pm$0.4 | 1 | 0.08
G0.054+0.027 |  | 24 | – | – | 0 | –
G0.014+0.021 |  | 25 | – | – | 0 | –
G0.001-0.058 | The 20 km/s cloud | 26 | 4.0$\pm$2.4 | 1.2$\pm$0.7 | 5 | 0.26
G359.948-0.052 | Sgr A*, circumnuclear disk | 27 | – | – | 0 | –
G359.889-0.093 | The 50 km/s cloud | 28 | 32.3$\pm$19.4 | 5.9$\pm$3.5 | 1 | 0.05
G359.865+0.022 |  | 29 | – | – | 0 | –
G359.734+0.002 |  | 30 | – | – | 0 | –
G359.648-0.133 |  | 31 | – | – | 0 | –
G359.611+0.018 |  | 32 | – | – | 0 | –
G359.615-0.243 |  | 33 | – | – | 0 | –
G359.484-0.132 | Sgr C | 34 | 65.4$\pm$39.2 | 15.4$\pm$9.2 | 3 | 0.60
G359.137+0.031 |  | 35 | – | – | 0 | –
Table 3: A version of Table 2 including ambiguously star-forming sources in addition to robustly star-forming sources. The first three columns include a coordinate name, colloquial name and cloud mask index for each cloud. The column “SFRHerschel” represents the star formation rate calculated in equation 5, assuming a dust temperature from Herschel, as reported in the catalog, with uncertainties due to star formation efficiency and random error in the mass estimation. The column “SFR50K” represents the star formation rate calculated in equation 5, assuming a dust temperature of 50K, with uncertainties due to star formation efficiency and random error in the mass estimation.The column “NSF” lists the number of robustly star-forming sources within each CMZoom cloud and the final column NSF/Ntot lists the fraction of sources with robust star formation tracers in each cloud. For clouds without star formation tracers, and for Sgr B2, these numbers are omitted and replaced with a dash.  Cloud ID | Colloquial Name | CMZoom | SFRHerschel | SFR50K | NSF | NSF/Ntot
---|---|---|---|---|---|---
|  | mask number | 10-3 M⊙yr-1 | 10-3 M⊙yr-1 |  |
G1.683-0.089 |  | 1 | – | – | 0 | –
G1.670-0.130 |  | 2 | 3.9$\pm$2.4 | 0.5$\pm$0.3 | 4 | 0.67
G1.651-0.050 |  | 3 | 1.5$\pm$0.9 | 0.2$\pm$0.1 | 1 | 0.50
G1.602+0.018 |  | 4 | 5.0$\pm$3.0 | 0.5$\pm$0.3 | 3 | 0.60
G1.085-0.027 |  | 5 | 7.1$\pm$4.2 | 1.1$\pm$0.6 | 3 | 1.00
G1.038-0.074 |  | 6 | – | – | 0 | –
G0.891-0.048 |  | 7 | – | – | 0 | –
G0.714-0.100 |  | 8 | 13.7$\pm$8.2 | 2.7$\pm$1.6 | 11 | 0.44
G0.699-0.028 | Sgr B2 | 9 | – | – | 0 | –
G0.619+0.012 | Sgr B2 SE | 10 | 32.0$\pm$19.2 | 8.6$\pm$5.2 | 8 | 0.80
G0.489+0.010 | Dust Ridge Clouds E&F | 11 | 16.9$\pm$10.1 | 2.9$\pm$1.8 | 3 | 0.23
G0.412+0.052 | Dust Ridge Cloud D | 12 | 2.7$\pm$1.6 | 0.5$\pm$0.3 | 2 | 0.17
G0.393-0.034 |  | 13 | – | – | 0 | –
G0.380+0.050 | Dust Ridge Cloud C | 14 | 38.7$\pm$23.2 | 10.2$\pm$6.1 | 3 | 0.38
G0.340+0.055 | Dust Ridge Cloud B | 15 | – | – | 0 | –
G0.326-0.085 | The Sailfish | 16 | 0.2$\pm$0.1 | 0.1$\pm$0.0 | 2 | 1.00
G0.316-0.201 |  | 17 | – | – | 0 | –
G0.253+0.016 | The Brick | 18 | 2.3$\pm$1.4 | 0.4$\pm$0.3 | 2 | 0.18
G0.212-0.001 |  | 19 | 5.3$\pm$3.2 | 1.6$\pm$1.0 | 4 | 0.80
G0.145-0.086 | The Straw Cloud | 20 | 0.4$\pm$0.3 | 0.1$\pm$0.1 | 1 | 0.50
G0.106-0.082 | The Sticks Cloud | 21 | – | – | 0 | –
G0.070-0.035 |  | 22 | 1.7$\pm$1.0 | 0.5$\pm$0.3 | 3 | 0.60
G0.068-0.075 | The Stone Cloud | 23 | 6.4$\pm$3.8 | 1.5$\pm$0.9 | 12 | 1.00
G0.054+0.027 |  | 24 | – | – | 0 | –
G0.014+0.021 |  | 25 | – | – | 0 | –
G0.001-0.058 | The 20 km/s cloud | 26 | 6.3$\pm$3.8 | 1.8$\pm$1.1 | 7 | 0.37
G359.948-0.052 | Sgr A*, circumnuclear disk | 27 | – | – | 0 | –
G359.889-0.093 | The 50 km/s cloud | 28 | 50.6$\pm$30.4 | 9.2$\pm$5.5 | 9 | 0.43
G359.865+0.022 |  | 29 | 0.1$\pm$0.1 | 0.0$\pm$0.0 | 1 | 0.50
G359.734+0.002 |  | 30 | 0.1$\pm$0.1 | 0.0$\pm$0.0 | 1 | 0.33
G359.648-0.133 |  | 31 | – | – | 0 | –
G359.611+0.018 |  | 32 | – | – | 0 | –
G359.615-0.243 |  | 33 | – | – | 0 | –
G359.484-0.132 | Sgr C | 34 | 65.4$\pm$39.2 | 15.4$\pm$9.2 | 3 | 0.60
G359.137+0.031 |  | 35 | – | – | 0 | –

The star formation rates of each CMZoom cloud are presented in Figure 7. Due
to the considerable uncertainties in the masses of the CMZoom sources within
the Sgr B2 complex and the circumnuclear field surrounding Sgr A*, we exclude
these two regions from our analysis (for more details on the issues with the
interpretation of these regions see section 5.1 of Hatchfield et al. (2020)
and section 5.4 of Battersby et al. (2020)). While low-mass star formation is
likely to occur throughout CMZ clouds both with and without star formation
tracers used in this work, we cannot know their star-forming properties. For
the excluded clouds and those with no high-mass star formation indicators, we
do not report a star formation rate, listing ‘—’ instead in Tables 2 and 3.

##  5 Discussion

###  5.1 Number Density, Column Density Ratio, and their Relationship to Star
Formation

Some theories and empirical models of star formation suggest the existence of
a volume density threshold (e.g. Krumholz & McKee, 2008; Kauffmann et al.,
2010; Lada et al., 2010, 2012; Padoan et al., 2014), below which molecular gas
cannot efficiently collapse and form new stars. Above this density threshold,
some of these theories and models predict an increase in the number of YSOs in
the cloud as a scaling relation, their YSO count and therefore star formation
rate increasing with density. The densities of all CMZoom sources appear to be
well above the surface and volume density thresholds suggested for solar
neighborhood clouds (e.g. Krumholz & McKee, 2008; Lada et al., 2010; Clark &
Glover, 2014). There is also evidence accumulating for the existence of an
environmentally dependent density threshold for star formation, which is
needed to explain the distribution of star formation observed in CMZ clouds
(e.g. Kauffmann et al., 2013; Kruijssen et al., 2014; Rathborne et al., 2014;
Kauffmann et al., 2017b; Walker et al., 2018; Barnes et al., 2019; Lu et al.,
2019a, b; Battersby et al., 2020). If there exists a universal density
threshold above which the amount of star formation increases in proportion to
the dense gas mass, we should expect to see a positively correlated scaling
relationship, or even a step function relating the density properties of the
catalog objects and the prevalence of ongoing star formation. If instead there
should be an environmentally dependent threshold, we might expect to see very
little star formation below some surface or volume density, and increasingly
more star formation above that threshold. Neither of these situations appears
to be the case for the CMZoom catalog objects.

In some cases, we do see correlations within the CMZoom sample. Figures 4 and
5 show the fraction of star-forming leaves across the range of physical
properties derived in Hatchfield et al. 2020. Three leaf properties do appear
to increase significantly along with the prevalence of robust star formation
indicators: the total leaf’s mass, leaf’s peak source-scale column density,
and the leaf’s column density ratio (the ratio of the source-scale peak column
density to the cloud-scale column density, $N_{\rm SMA}/N_{\rm Herschel}$).
The uptick in frequency of star-forming leaves that occurs for both mass and
peak source-scale column density is largely due to a very small number of
leaves in high-mass and high-column density bins, corresponding to the handful
of already well-known and well-studied young massive clusters in the CMZ (Dust
Ridge Cloud C, Sgr C).

The sharp rise in the prevalence of robustly star-forming sources that occurs
above a column density ratio of $\sim 1.5$ N${}_{\rm SMA}/$NHerschel comes
from a significantly larger sample of sources (N$>$30), including a
combination of well-studied regions and previously understudied clouds.
Therefore, column density ratio seems to correlate most significantly with the
presence of active star formation. The correlation of column density ratio
with the indicators of active star formation is not necessarily surprising
(e.g. Kruijssen et al., 2014), as the conditions for active star formation
demand the presence of local, gravitationally bound overdensities. Figure 6
shows the stark contrast between distribution of star formation within leaves
as a function of volume density and of column density ratio. While star
formation does occur in sources across the range of volume densities and
column density ratios probed by CMZoom, the vast majority (over $\sim$75%) of
leaves above a column density ratio of $\sim 1.5$ have tracers of star
formation. It is possible that this number represents a threshold in the
relative surface density, above which turbulent fluctuations are increasingly
likely to produce substructures that are dense enough to form stars. While
star formation can occur in sources with low column density ratio, any
substructure in excess of this column density ratio threshold is extremely
likely to be gravitationally bound and actively be forming stars. However,
from this study alone it is not possible to determine if this threshold is
dependent on the observational parameters of the data used to construct the
column density ratio estimate. It is therefore unclear if this can be
generalized to a dense gas fraction threshold on similar spatial scales, and
further analysis will elucidate its relevance to other surveys of dense
substructure in molecular clouds.

Notably, there is no corresponding correlation of star formation tracer
prevalence with the volume density of these sources. The lack of such a
correlation with density begs the question - why are stars not preferentially
forming in the highest density substructures? It is possible that the
assumptions that we use to derive the leaf volume densities are overly-
simplistic and fail to accurately represent the importance of the ISM’s three-
dimensional complexity. For instance, we assume that the mass derived from
each dendrogram leaf’s integrated flux is spherically distributed, isotropic
in both the plane-of-the-sky and along the line of sight. While leaves in the
catalog are not uniformly circular, equation 3 uses the effective radius of
each leaf to calculate an average volume density. Densities on the physical
scales of the CMZoom are certain to have non-uniformities, and the unresolved
substructure of the leaves complicates their interpretation.

Clark & Glover 2014 used hydrodynamic simulations of star-forming clouds to
evaluate the efficacy of translating between measured column density and the
true volume density of star-forming regions to evaluate star formation density
thresholds, finding that the mass of clouds above a given column density does
not translate straightforwardly to a mass above a corresponding measured
volume density. The average density of a clump-scale object has an
inconvenient degeneracy. When averaging over an entire structure composed of
unresolved quiescent or star-forming substructure, the mean volume density may
represent a log-normal distribution due to the turbulent velocity and density
field (as is predicted in the substantial theoretical literature of turbulent
molecular clouds, e.g. Burkhart & Mocz 2019; Chen et al. 2018) or it may
represent a more diffuse envelope embedding a collection of gravitationally
bound cores at very high volume density. Since we cannot distinguish between
these scenarios with the mean volume density, one which may either represent a
quiescent, turbulent structure or an actively star-forming object, we should
not expect mean volume density to consistently correlate with star formation
tracers. In this way of thinking, the peak SMA column density and the column
density ratio are better suited to distinguish between a dense, but unbound
structure and an actively star-forming protocluster. This helps to explain why
the column density ratio, in the bottom left panel of Figure 5 shows the most
robust correlation with active star formation tracers.

It is also possible that the densities measured are an adequate probe of the
true volume densities of the sources, and the lack of correlation between
volume density and tracers of active star formation is representative of the
physical timescales relevant to star formation. The timescales required for
protostars to exhibit the star formation tracers used in this work (far
infrared radiation from heated gas envelopes and masers) are not well
constrained. The flux from which we measure the volume density is not
necessarily from material that will form stars, but perhaps also represents
gas that is actively escaping the process of star formation. Simultaneously,
many of the dense sources that do not exhibit any indication of star formation
may truly be pre-stellar gas structures, so the “robustly non-star-forming”
sources may be contributing to future star formation in a way that is not
well-constrained by this procedure. Higher resolution observations and virial
analysis (e.g. Myers et al., 2022) provide more insight into what component of
the gas in these structures should be treated as star-forming or quiescent,
though very few sources seem to be entirely gravitationally bound according to
recent sprectral analysis presented by Callanan et al. (2023).

Figure 6: The distribution of robustly star-forming, robustly quiescent, and
ambiguous CMZoom catalog leaves as a function of $n$(H2), the volume number
density of H2, and the column density ratio, defined as the ratio of the SMA-
derived source-scale column density to the Herschel-derived cloud-scale column
density for each source. The colorscale background represents the ratio of
star-forming leaves to all leaves in each bin. While leaves with signatures of
active star formation occur at both low and high number densities and column
density ratios, a sharp uptick in the fraction of star-forming sources occurs
at a column density ratio threshold of $\sim$ 1.5 (or log10(Column Density
Ratio) $\approx$ 0.17). There is no obvious scaling between volume density and
active star formation. Figure 7: The range of star formation rates from
robustly star-forming sources and uncertainties derived using a variable dust
temperature in calculating source masses, using only robust star formation
indicators. In each panel, the black bar represents the star formation rate
from equation 5 for physical properties calculated using a range of assumed
dust temperatures from the Herschel-derived estimate reported in the catalog
to a constant 50K. The error bars in each panel represent the uncertainty due
to, from left to right, random uncertainties (including local noise in the
measured submillimeter flux, assumed distance, and dust temperature
fluctuations), the variation due to our choice of star formation efficiency,
and lastly the uncertainty in the local dust properties of each source. The
lower limit on the SFR from Sgr B2 is shown in green using the constraining
values presented in Ginsburg et al. (2018). Figure 8: A version of Figure 7
that also includes ambiguously star-forming sources. Again, in each panel, the
black bar represents the star formation rate from equation 5 for physical
properties calculated using a range of assumed dust temperatures from the
Herschel-derived estimate reported in the catalog to a constant 50K. The error
bars in each panel represent the uncertainty due to, from left to right,
random uncertainties (including local noise in the measured submillimeter
flux, assumed distance, and dust temperature fluctuations), the variation due
to our choice of star formation efficiency, and lastly the uncertainty in the
local dust properties of each source. The lower limit on the SFR from Sgr B2
is shown in green using the constraining values presented in Ginsburg et al.
(2018).

###  5.2 The Relationship Between Tracers of High-Mass Star Formation and the
Total Star Formation Rate of CMZ Clouds

Given the completeness of the CMZoom catalog to sites of incipient high-mass
star formation, the star formation rates presented in this work effectively
incorporate all possible deeply-embedded high-mass star formation in the CMZ.
If we wish to understand this subset of the star-forming population in the
context of the holistic star formation properties of the Galactic Center and
calculate an incipient star formation rate for the CMZ as a whole, we must
carefully consider our assumptions about the star formation activity and the
protostellar population for which these tracers are not sensitive.

Firstly, the protostellar ages of these star-forming objects are not well
constrained. As dense gas in the CMZ’s molecular clouds collapses, some local
density maxima will achieve the conditions for gravitational instability and
collapse to form clusters of stars. The high-mass protostars heat the gas and
dust around them and add substantial energy into the surrounding ISM, leading
to the emission that we use as a tracer of star formation in this work.
Feedback from massive stars in these clusters will begin to erode the cold,
submillimeter-bright envelope embedding the cluster as photodissociation
regions emerge. Therefore, if we see signatures of active high-mass star
formation such as methanol masers or compact dust emission in the far infrared
associated with the densest submillimeter bright substructure within a cloud,
we know that this star formation has not progressed long enough to destroy or
significantly displace its natal envelope. While the amount of time needed for
massive YSOs to destroy their envelope is not yet precisely understood and is
likely to vary by environment, it is believed that it takes on the order of
$\sim 4\times 10^{5}$ years (Davies et al., 2011). Therefore we anticipate
that the sources identified in this work probe a range of protostellar ages
less than $\sim 4\times 10^{5}$ years.

The sample of previously catalogued YSOs used in this work (An et al., 2011;
Yusef-Zadeh et al., 2009; Immer et al., 2012) contains many sources that do
not correspond to CMZoom catalog sources, likely either representing evolved
stellar contaminants or more evolved young high-mass stars that have already
destroyed the cold dense components of their envelopes. The presence of a YSO
candidate in the absence of compact submillimeter emission, given the
completeness of CMZoom, implies that these sources are more advanced in their
protostellar evolution. Therefore we expect that CMZoom-associated star
formation signatures are tracing a more specific, younger population of
protostellar sources, which is how we define the term “incipient” star
formation throughout this work.

As discussed briefly in Section 4, the cloud star formation rates that we
calculate according to equation 5 rely on ill-constrained assumptions about
the star formation efficiency per free-fall time on these spatial scales and
missing lower-mass star formation within the clouds. Given the diverse
morphologies and star formation signatures of CMZoom sources, we adopted a
range for star formation efficiency per free-fall time, $0.1\leq\epsilon_{\rm
SF}\leq 0.4$ with a fiducial value of 0.25. It is not possible to make a more
specific correction due to the IMF than the one used in equation 5 without a
thorough analysis of the low-mass YSO population of the CMZ, which is beyond
the capabilities of the present data set but may be feasible with future,
higher resolution and sensitivity observations. There are reports of a top-
heavy IMF in the known Galactic Center young star clusters- namely the Arches,
Quintuplet, and Young Nuclear clusters (e.g. Hosek et al., 2019; Rui et al.,
2019). While it is still unclear if an abnormal slope is characteristic of
nascent CMZ star clusters or high-mass clusters in general, any variation in
the typical IMF will influence the assumptions used in calculating these SFRs.
A universally top-heavy IMF would imply that the values presented in this work
would be overestimates of the true SFRs of CMZ clouds.

With the context of these significant uncertainties, we can estimate the total
star formation rate of the Galactic Center, excluding the circumnuclear disk.
Summing over the clouds’ star formation rates derived in Section 4.2, using
our assumed star formation efficiency $\epsilon_{\rm SF}=0.25\pm 0.15$, the
IMF correction described in Section 4.2, and assuming an elevated dust
temperature of 50K, we find an incipient CMZ SFR of $\sim$0.08 M⊙ yr-1 across
the 13 robustly star-forming CMZoom clouds. This value includes the star
formation rate for Sgr B2 calculated by Ginsburg et al. (2018) of 0.036 M⊙
yr-1, since the CMZoom observations of the corresponding region are difficult
to interpret due to the local noise properties (see section 5 of Hatchfield et
al. (2020) for more details). However, if the dust temperatures on 0.1 pc
scales near star-forming sources are closer to the Herschel-calculated dust
temperatures, the masses used in equation 5 are considerably higher. Including
the sources with ambiguous star formation tracers (detailed in Section 3.2),
and with those lower dust temperatures reported in the catalog, we find a
higher total CMZ SFR of $\sim$0.45 M⊙ yr-1 across 20 robustly and ambiguously
star-forming CMZoom clouds, which is remarkably similar to the empirical dense
gas scaling relation-derived value for the CMZ’s SFR ($\sim$ 0.46 M⊙ yr-1)
presented in Lu et al. 2019a.

###  5.3 Is Star Formation in the Central Molecular Zone Episodic?

Previous studies of the CMZ SFR using methods including YSO counting, HII
region counting, and integrated light measurements find a CMZ SFR with mean
value computed by Henshaw et al. (2022) of 0.07${}^{+0.08}_{-0.02}$. As stated
above, this is in line with our fiducial SFR value of $\sim$0.08 M⊙ yr-1.
However, our fiducial value does not include any ambiguously star-forming
sources, and assumes higher dust temperatures than those measured with
Herschel, along with a star formation efficiency which is very ill-constrained
for sources on these spatial scales. If we include the ambiguously star-
forming sources, and a higher star formation efficiency of 0.4, equation 5
yields a much higher star formation rate of 0.45 M⊙ yr-1, which we can
interpret as an upper limit (excluding the uncertainty from the dust
temperatures). If these assumed higher values are reasonable and the majority
of the ambiguously star-forming sources do host a high-mass protostellar
activity, this implies the star formation rate of the CMZ is increasing.

There is both theoretical and observational precedent for large fluctuations
in the Galactic Center’s SFR. Within such a model for the CMZ’s evolution, the
dearth of recent star formation is the result of episodic fluctuations, being
preceded and followed by periods of enhanced star formation (e.g. Kruijssen et
al., 2014; Krumholz & Kruijssen, 2015; Armillotta et al., 2019; Orr et al.,
2021). As described in more detail in Section 3.2 of Henshaw et al. (2022),
there is increasing observational evidence to suggest that the SFR of the CMZ
has varied significantly on timescales of tens of Myr (given the stellar
masses and ages of the Arches and Quintuplet clusters) and on timescales of
hundreds of Myr. Lu et al. (2019b) suggested that the SFR of the CMZ may show
signs of imminently increasing from its present value. In recent work
analyzing the stellar age distribution of the nuclear stellar disk, Nogueras-
Lara et al. (2020) showed that the SFR in the inner few hundred parsecs has
reached higher values of $\sim$0.5 M⊙ yr-1 within the last Gyr, similar to the
upper limit SFR of 0.45 M⊙ yr-1 calculated in this work.

A recent census of the CMZ’s high-mass star formation using VLA C-band
observations of ultra-compact HII regions and methanol masers presented in Lu
et al. 2019a finds a lower limit SFR of $\sim$0.025 M⊙ yr-1 for the Galactic
Center. The calculation of this value assumes a characteristic timescale of
0.3 Myr and a total stellar mass extrapolated from the IMF. The discrepancy
between this and the value presented in our analysis may be due to a
difference in the timescale and phase of star formation traced by both methods
(the median freefall time for star-forming sources in the CMZoom catalog is
0.1 Myr). It is likely that much of the star-forming mass we characterize in
this work represents more recent and future star formation, not necessarily
associated with observed masers and observable ultra-compact HII regions.

Alternatively, we can calculate a much more conservative estimate of the star
formation rate to act as a lower limit on the CMZ’s SFR by neglecting the IMF
correction and only considering the mass derived from the observed, robustly
star-forming objects. This lower limit value still depends on the choice of
star formation efficiency and dust temperature, and as such must still be
interpreted with caution. Neglecting the IMF correction, and with an assumed
dust temperature of 50K and a low star formation efficiency of 10%, we find a
total SFR (excluding the CND) of $\sim$0.05 M⊙ yr-1, the majority of which is
due to the estimate of the SFR of Sgr B2 ($\sim$0.036 M⊙ yr-1, from Ginsburg
et al. (2018)). This lower limit lies much closer to previous estimates of the
CMZ’s SFR. The most significant sources of uncertainty in the measurements of
cloud SFRs remain the dust opacity, dust temperature, and star formation
efficiency described in Section 4 and shown in Figure 7.

###  5.4 The Nature of Atoll Structures in Dense Submillimeter Gas

Figure 9: An example of the “atoll” morphology of dust continuum sources
observed by CMZoom, shown in the three color images used for the by-eye
classification procedure detailed in Section 3.2. These dust ring
configurations are likely to represent remaining gas surrounding young HII
regions. The three colors used in the top panel are 8$\mu$m (blue, GLIMPSE,
from Benjamin et al. (2003), 24$\mu$m (green, MIPSGAL, from Carey et al.
2009), and 70$\mu$m (red, Hi-Gal, from Molinari et al. (2010)). These are each
shown individually in the bottom four panels, along with the 21$\mu$m emission
from MSX (Egan et al., 2003). Overlaid on the composite three-color image are
white contours outlining the CMZoom leaves, along with cyan circles
demarcating YSO candidates from a compilation of those identified by Yusef-
Zadeh et al. (2009), An et al. (2011), and Immer et al. (2012), purple circles
indicating the 70$\mu$m point sources catalogued by Molinari et al. (2010),
and darker blue circles representing the point sources identified by Gutermuth
& Heyer (2015). The radial size of these circles corresponds to the FWHM
condition used do determine plausible association with CMZoom leaves. The
bottom panel shows a 70$\mu$m mosaic of the Galactic Center with each CMZoom
region shown as black box, with the specific region from the above panels
highlighted in red.

Amidst the wealth of dense gas morphologies observed throughout the sample of
CMZ clouds, several regions exhibit a common pattern of dense submillimeter
sources clustered surrounding a more evolved source, reminiscent of an atoll
of cold gas islands enclosing an far-infrared bright lagoon. These “atoll
sources” occur in several clouds surveyed by CMZoom, an example of which is
shown in Figure 9. Atoll sources are flagged by-eye, as their morphology
varies significantly from region to region. It is not obvious that these
sources represent a common physical phenomenon or several different phenomena
which appear similar on the plane of the sky. Line-of-sight projection issues
rule out any attempt to estimate a completeness to these types of sources, and
it is possible that other sources in the catalog would appear as atoll sources
from other viewing angles. It is possible that these sources only appear in
proximity to their central “lagoon” of compact infrared emission due to plane-
of-the-sky projection effects.

In several cases where higher-resolution ALMA data are available, these
sources appear to be rings of dense gas surrounding an extended HII region,
and therefore represent an interesting phase of molecular cloud evolution. At
this point, stellar feedback from young stars is actively eroding away their
natal envelopes, though it is unclear how long this phase lasts. Parsec-scale
bubbles are found in simulations (e.g. Rosen et al., 2021) and observations
(e.g. Feddersen et al., 2018) of regions of recent and ongoing star formation,
and the lingering presence of a detectable cold dust component to their
spectral energy distributions may help to constrain their protostellar age and
class. Presently, our criteria for identifying these structures are
qualitative and a common physical interpretation cannot be argued here, so we
aim to simply note their presence and their potential significance. Future
work will investigate the properties of these atoll sources and their central
HII region lagoons in the combined context of their continuum and spectral
properties, taking into account the submillimeter emission along with radio
continuum observations using the VLA.

##  6 Summary

The CMZ hosts a diverse population of giant molecular clouds with different
morphologies and fragmented structures, and provides a unique opportunity to
study the formation of stars in a more extreme environment than the Galactic
Disk. The CMZoom survey has allowed us to resolve the sub-parsec substructure
of all dense material throughout the CMZ. By comparing the highly-complete
catalog of dense submillimeter sources from this survey with previous wide
surveys of signatures of high-mass star formation, we are able to characterize
all possible sites of ongoing, deeply embedded high-mass star formation in the
Galactic Center, excluding Sgr B2 and the circumnuclear disk. In this work, we
have cross-referenced the CMZoom catalog of submillimeter-bright substructure
with catalogs of YSO candidates (Yusef-Zadeh et al., 2009; An et al., 2011;
Immer et al., 2012) and catalogs of far infrared point sources (Gutermuth &
Heyer, 2015; Molinari et al., 2016). We also catalogued compact emission
localized with the CMZoom catalog leaves in maps of 8µm and 24µm maps from
Spitzer, 21µm maps from MSX, 25 and 37µm maps from SOFIA’s FORCAST instrument,
and 70µm emission from Herschel by-eye. The key results from our analysis are:

  * •

Of the objects catalogued by CMZoom (excluding the Sgr B2 complex and the CND
region surrounding Sgr A*), 39 show robust signatures of ongoing high-mass
star formation (a maser, previously identified YSO, or by-eye identified 24
and/or 70$\mu$m compact source), while 57 others show ambiguous signatures
which may or may not be associated with active star formation. The remaining
103 leaves appear presently robustly quiescent, either representing a very
early a stage of gravitational collapse without thermal emission in the far-
infrared, or representing transient, turbulent density fluctuations in the the
CMZ’s molecular clouds.

  * •

Assuming a range of star formation efficiencies and local dust temperatures,
we calculate a cloud-by-cloud SFR for each region in the CMZoom footprint,
sensitive to all sites of recent ($\lesssim 4\times 10^{5}$ yr) and incipient
high-mass star formation in the CMZ. Combining these cloud star formation
rates, we estimate an incipient SFR for the entire CMZ of $\sim 0.08$ M⊙ yr-1.
We calculate an upper limit CMZ SFR of $\sim 0.45$ M⊙ yr-1, including more
ambiguously star-forming sources, using lower dust temperature estimates and a
higher assumed star formation efficiency. These SFRs are higher than some
previous measurements of the CMZ’s SFR averaged over longer time scales
(considerably higher in the lower dust temperature case), suggesting the
possibility of an imminent increase in the Galactic Center’s star formation
rate.

  * •

CMZ sources with higher volume densities are not more likely to host ongoing
high-mass star formation. This implies either that denser material is not
necessarily more likely to host high-mass star formation, that the densities
measured do not accurately represent the densities of the pre-stellar
envelope, or that our observational assumptions used to derive a 3D density
from the objects’ 1.3mm dust continuum emission are significantly flawed.
Upcoming work constraining gas densities within the CMZoom leaves will help
resolve this ambiguity.

  * •

The gas column density ratio (NSMA(H2)/ NHerschel(H${}_{2})$) tends to be
higher in regions where high-mass stars are actively forming, particularly
above a threshold of NSMA(H2)/NHerschel(H${}_{2})$ $\gtrsim 1.5$. It is
unclear if this threshold is dependent on the physical scales probed by these
particular observations, and thus it should be interpreted with caution.

  * •

We identify the common morphology of “atoll” sources, ring-like structures of
dense gas surrounding an evolved, far infrared-bright source, resembling a
string of islands around a lagoon. Some of these sources correspond to the
outskirts of known HII regions. Thus, we suspect these systems represent a
particular stage of high-mass star formation, in which the HII region of a
newborn high-mass star is in the process of destroying its natal envelope, and
the continuum sources detected are the remaining pockets of dense gas which
may or may not host ongoing or future star formation. These atoll sources may
be valuable targets for follow-up study.

While a great deal of uncertainty remains about the present, past, and future
of the CMZ’s star formation rate, the expansion and analysis of the CMZoom
catalog presented in and published with this work constrains both lower and
upper limits on the incipient cloud-by-cloud and whole-CMZ star formation
properties. Future observational work will aim to characterize the nature of
the ambiguously star-forming sources in the catalog, further constrain dust
and gas temperatures on more relevant spatial scales, and better resolve the
low-mass component of the CMZ’s YSO population. Simultaneously, further
efforts are likely to allow better estimation of a relevant star formation
efficiency. As our understanding improves, the results from this catalog will
continue to constrain the CMZ’s star formation properties, guiding future
observations and interpretation of the Galactic Center’s evolution.

We would like to thank the anonymous reviewer for their insightful comments
which substantially improved the quality of this work. HPH’s research was
supported by an appointment to the NASA Postdoctoral Program administered by
Oak Ridge Associated Universities under contract with NASA. HPH was supported
by JPL, which is run under contract by California Institute of Technology for
NASA. HPH gratefully acknowledges support for this work from the SOFIA
Archival Research Program (program ID 09_0540). HPH also thanks the LSSTC Data
Science Fellowship Program, which is funded by LSSTC, NSF Cybertraining grant
#1829740, the Brinson Foundation, and the Moore Foundation; his participation
in the program has benefited this work. Additionally, HPH gratefully
acknowledges support from the National Science Foundation under Award No.
1816715. EACM gratefully acknowledges support by the National Science
Foundation under grant No. AST-1813765. AG acknowledges support from NSF
grants AST 2008101 and CAREER 2142300. CB gratefully acknowledges funding from
National Science Foundation under Award Nos. 1816715, 2108938, 2206510, and
CAREER 2145689, as well as from the National Aeronatics and Space
Administration through the Astrophysics Data Analaysis Program under Award No.
21-ADAP21-0179 and through the SOFIA archival research program under Award No.
09$\\_$0540\. ATB would like to acknowledge funding from the European Research
Council (ERC) under the European Union’s Horizon 2020 research and innovation
programme (grant agreement No.726384/Empire). JMDK gratefully acknowledges
funding from the European Research Council (ERC) under the European Union’s
Horizon 2020 research and innovation programme via the ERC Starting Grant
MUSTANG (grant agreement number 714907). COOL Research DAO is a Decentralized
Autonomous Organization supporting research in astrophysics aimed at
uncovering our cosmic origins. LCH was supported by the National Science
Foundation of China (11721303, 11991052, 12011540375, 12233001) and the China
Manned Space Project (CMS-CSST-2021-A04, CMS-CSST-2021-A06). Herschel is an
ESA space observatory with science instruments provided by European-led
Principal Investigator consortia and with important participation from NASA.

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##  Appendix A Gallery of Three-color Images Used in Star Formation Tracer
Search

This appendix contains the complete gallery of three-color images used to
assess the star formation status of each leaf in the CMZoom robust catalog in
Figures 10 - 33. The red colorscale shows the 70$\mu$m emission map from
Herschel (Molinari et al., 2010, 2011). The green colorscale shows the
combined 21 and 24$\mu$m emission from MSX and Spitzer respectively (Benjamin
et al., 2003). The blue colorscale shows the 8$\mu$m map from Spitzer
(Benjamin et al., 2003). Each color is shown in logscale, scaled between a
local 5% and 95% boundary value for each box. Overlaid on the composite three-
color image are white contours representing the CMZoom leaves, along with cyan
circles representing YSO candidates from a compilation of those identified by
Yusef-Zadeh et al. 2009, An et al. 2011, and Immer et al. 2012, purple circles
representing the 70$\mu$m point sources cataloged by Molinari et al. 2016, and
darker blue circles representing the point sources identified by Gutermuth &
Heyer 2015. The radial size of these circles corresponds to the FWHM condition
used to determine plausible association with nearby CMZoom leaves. Region
numbers used in this section do not correspond to the mask numbers referenced
in the tables throughout the rest of this work.

Figure 10: Region 1, Cloud ID G0.253+0.016, also known as The Brick. The red
colorscale shows the 70$\mu$m emission map from Herschel (Molinari et al.,
2010, 2011). The green colorscale shows the combined 21 and 24$\mu$m emission
from MSX and Spitzer respectively (Benjamin et al., 2003). The blue colorscale
shows the 8$\mu$m map from Spitzer (Benjamin et al., 2003). Each color is
shown in logscale, scaled between a local 5% and 95% boundary value for each
box. Overlaid on the composite three-color image are white contours
representing the CMZoom leaves, along with cyan circles representing YSO
candidates from a compilation of those identified by Yusef-Zadeh et al. 2009,
An et al. 2011, and Immer et al. 2012, purple circles representing the
70$\mu$m point sources cataloged by Molinari et al. 2016, and darker blue
circles representing the point sources identified by Gutermuth & Heyer 2015.
The radial size of these circles corresponds to the FWHM condition used to
determine plausible association with nearby CMZoom leaves. Figure 11: Region
2, Cloud ID G0.070-0.035. The red colorscale shows the 70$\mu$m emission map
from Herschel (Molinari et al., 2010, 2011). The green colorscale shows the
combined 21 and 24$\mu$m emission from MSX and Spitzer respectively (Benjamin
et al., 2003). The blue colorscale shows the 8$\mu$m map from Spitzer
(Benjamin et al., 2003). Each color is shown in logscale, scaled between a
local 5% and 95% boundary value for each box. Overlaid on the composite three-
color image are white contours representing the CMZoom leaves, along with cyan
circles representing YSO candidates from a compilation of those identified by
Yusef-Zadeh et al. 2009, An et al. 2011, and Immer et al. 2012, purple circles
representing the 70$\mu$m point sources cataloged by Molinari et al. 2016, and
darker blue circles representing the point sources identified by Gutermuth &
Heyer 2015. The radial size of these circles corresponds to the FWHM condition
used to determine plausible association with nearby CMZoom leaves. Figure 12:
Region 3, Cloud ID G0.145-0.086, also known as the Straw Cloud. The red
colorscale shows the 70$\mu$m emission map from Herschel (Molinari et al.,
2010, 2011). The green colorscale shows the combined 21 and 24$\mu$m emission
from MSX and Spitzer respectively (Benjamin et al., 2003). The blue colorscale
shows the 8$\mu$m map from Spitzer (Benjamin et al., 2003). Each color is
shown in logscale, scaled between a local 5% and 95% boundary value for each
box. Overlaid on the composite three-color image are white contours
representing the CMZoom leaves, along with cyan circles representing YSO
candidates from a compilation of those identified by Yusef-Zadeh et al. 2009,
An et al. 2011, and Immer et al. 2012, purple circles representing the
70$\mu$m point sources cataloged by Molinari et al. 2016, and darker blue
circles representing the point sources identified by Gutermuth & Heyer 2015.
The radial size of these circles corresponds to the FWHM condition used to
determine plausible association with nearby CMZoom leaves. Figure 13: Region
4, including Cloud IDs G0.068-0.075 and G0.106-0.082, also known as the Sticks
Cloud and the Stone Clouds respectively. The red colorscale shows the 70$\mu$m
emission map from Herschel (Molinari et al., 2010, 2011). The green colorscale
shows the combined 21 and 24$\mu$m emission from MSX and Spitzer respectively
(Benjamin et al., 2003). The blue colorscale shows the 8$\mu$m map from
Spitzer (Benjamin et al., 2003). Each color is shown in logscale, scaled
between a local 5% and 95% boundary value for each box. Overlaid on the
composite three-color image are white contours representing the CMZoom leaves,
along with cyan circles representing YSO candidates from a compilation of
those identified by Yusef-Zadeh et al. 2009, An et al. 2011, and Immer et al.
2012, purple circles representing the 70$\mu$m point sources cataloged by
Molinari et al. 2016, and darker blue circles representing the point sources
identified by Gutermuth & Heyer 2015. The radial size of these circles
corresponds to the FWHM condition used to determine plausible association with
nearby CMZoom leaves. Figure 14: Region 5, Cloud ID G0.070-0.035 and
G0.001-0.058 (also known as the 20 km s-1 Cloud). The red colorscale shows the
70$\mu$m emission map from Herschel (Molinari et al., 2010, 2011). The green
colorscale shows the combined 21 and 24$\mu$m emission from MSX and Spitzer
respectively (Benjamin et al., 2003). The blue colorscale shows the 8$\mu$m
map from Spitzer (Benjamin et al., 2003). Each color is shown in logscale,
scaled between a local 5% and 95% boundary value for each box. Overlaid on the
composite three-color image are white contours representing the CMZoom leaves,
along with cyan circles representing YSO candidates from a compilation of
those identified by Yusef-Zadeh et al. 2009, An et al. 2011, and Immer et al.
2012, purple circles representing the 70$\mu$m point sources cataloged by
Molinari et al. 2016, and darker blue circles representing the point sources
identified by Gutermuth & Heyer 2015. The radial size of these circles
corresponds to the FWHM condition used to determine plausible association with
nearby CMZoom leaves. Figure 15: Region 6, Cloud ID G0.340+0.055, also known
as Dust Ridge Cloud B. The red colorscale shows the 70$\mu$m emission map from
Herschel (Molinari et al., 2010, 2011). The green colorscale shows the
combined 21 and 24$\mu$m emission from MSX and Spitzer respectively (Benjamin
et al., 2003). The blue colorscale shows the 8$\mu$m map from Spitzer
(Benjamin et al., 2003). Each color is shown in logscale, scaled between a
local 5% and 95% boundary value for each box. Overlaid on the composite three-
color image are white contours representing the CMZoom leaves, along with cyan
circles representing YSO candidates from a compilation of those identified by
Yusef-Zadeh et al. 2009, An et al. 2011, and Immer et al. 2012, purple circles
representing the 70$\mu$m point sources cataloged by Molinari et al. 2016, and
darker blue circles representing the point sources identified by Gutermuth &
Heyer 2015. The radial size of these circles corresponds to the FWHM condition
used to determine plausible association with nearby CMZoom leaves. Figure 16:
Region 7, Cloud ID G0.380+0.050, also known as Dust Ridge Cloud C. The red
colorscale shows the 70$\mu$m emission map from Herschel (Molinari et al.,
2010, 2011). The green colorscale shows the combined 21 and 24$\mu$m emission
from MSX and Spitzer respectively (Benjamin et al., 2003). The blue colorscale
shows the 8$\mu$m map from Spitzer (Benjamin et al., 2003). Each color is
shown in logscale, scaled between a local 5% and 95% boundary value for each
box. Overlaid on the composite three-color image are white contours
representing the CMZoom leaves, along with cyan circles representing YSO
candidates from a compilation of those identified by Yusef-Zadeh et al. 2009,
An et al. 2011, and Immer et al. 2012, purple circles representing the
70$\mu$m point sources cataloged by Molinari et al. 2016, and darker blue
circles representing the point sources identified by Gutermuth & Heyer 2015.
The radial size of these circles corresponds to the FWHM condition used to
determine plausible association with nearby CMZoom leaves. Figure 17: Region
8, Cloud ID G0.412+0.052, also known as Dust Ridge Cloud D. The red colorscale
shows the 70$\mu$m emission map from Herschel (Molinari et al., 2010, 2011).
The green colorscale shows the combined 21 and 24$\mu$m emission from MSX and
Spitzer respectively (Benjamin et al., 2003). The blue colorscale shows the
8$\mu$m map from Spitzer (Benjamin et al., 2003). Each color is shown in
logscale, scaled between a local 5% and 95% boundary value for each box.
Overlaid on the composite three-color image are white contours representing
the CMZoom leaves, along with cyan circles representing YSO candidates from a
compilation of those identified by Yusef-Zadeh et al. 2009, An et al. 2011,
and Immer et al. 2012, purple circles representing the 70$\mu$m point sources
cataloged by Molinari et al. 2016, and darker blue circles representing the
point sources identified by Gutermuth & Heyer 2015. The radial size of these
circles corresponds to the FWHM condition used to determine plausible
association with nearby CMZoom leaves. Figure 18: Region 9, Cloud ID
G0.489+0.010, otherwise known as Dust Ridge Clouds E and F. The red colorscale
shows the 70$\mu$m emission map from Herschel (Molinari et al., 2010, 2011).
The green colorscale shows the combined 21 and 24$\mu$m emission from MSX and
Spitzer respectively (Benjamin et al., 2003). The blue colorscale shows the
8$\mu$m map from Spitzer (Benjamin et al., 2003). Each color is shown in
logscale, scaled between a local 5% and 95% boundary value for each box.
Overlaid on the composite three-color image are white contours representing
the CMZoom leaves, along with cyan circles representing YSO candidates from a
compilation of those identified by Yusef-Zadeh et al. 2009, An et al. 2011,
and Immer et al. 2012, purple circles representing the 70$\mu$m point sources
cataloged by Molinari et al. 2016, and darker blue circles representing the
point sources identified by Gutermuth & Heyer 2015. The radial size of these
circles corresponds to the FWHM condition used to determine plausible
association with nearby CMZoom leaves. Figure 19: Region 10, Cloud ID
G0.699-0.028, also known as Sgr B2. The red colorscale shows the 70$\mu$m
emission map from Herschel (Molinari et al., 2010, 2011). The green colorscale
shows the combined 21 and 24$\mu$m emission from MSX and Spitzer respectively
(Benjamin et al., 2003). The blue colorscale shows the 8$\mu$m map from
Spitzer (Benjamin et al., 2003). Each color is shown in logscale, scaled
between a local 5% and 95% boundary value for each box. Overlaid on the
composite three-color image are white contours representing the CMZoom leaves,
along with cyan circles representing YSO candidates from a compilation of
those identified by Yusef-Zadeh et al. 2009, An et al. 2011, and Immer et al.
2012, purple circles representing the 70$\mu$m point sources cataloged by
Molinari et al. 2016, and darker blue circles representing the point sources
identified by Gutermuth & Heyer 2015. The radial size of these circles
corresponds to the FWHM condition used to determine plausible association with
nearby CMZoom leaves. Figure 20: Region 11, Cloud ID G0.619+0.012, also known
as Sgr B2 SE. The red colorscale shows the 70$\mu$m emission map from Herschel
(Molinari et al., 2010, 2011). The green colorscale shows the combined 21 and
24$\mu$m emission from MSX and Spitzer respectively (Benjamin et al., 2003).
The blue colorscale shows the 8$\mu$m map from Spitzer (Benjamin et al.,
2003). Each color is shown in logscale, scaled between a local 5% and 95%
boundary value for each box. Overlaid on the composite three-color image are
white contours representing the CMZoom leaves, along with cyan circles
representing YSO candidates from a compilation of those identified by Yusef-
Zadeh et al. 2009, An et al. 2011, and Immer et al. 2012, purple circles
representing the 70$\mu$m point sources cataloged by Molinari et al. 2016, and
darker blue circles representing the point sources identified by Gutermuth &
Heyer 2015. The radial size of these circles corresponds to the FWHM condition
used to determine plausible association with nearby CMZoom leaves. Figure 21:
Region 12, Cloud IDs G0.699-0.028 and G0.619+0.012, also known as Sgr B2 and
Sgr B2 SE respectively. The red colorscale shows the 70$\mu$m emission map
from Herschel (Molinari et al., 2010, 2011). The green colorscale shows the
combined 21 and 24$\mu$m emission from MSX and Spitzer respectively (Benjamin
et al., 2003). The blue colorscale shows the 8$\mu$m map from Spitzer
(Benjamin et al., 2003). Each color is shown in logscale, scaled between a
local 5% and 95% boundary value for each box. Overlaid on the composite three-
color image are white contours representing the CMZoom leaves, along with cyan
circles representing YSO candidates from a compilation of those identified by
Yusef-Zadeh et al. 2009, An et al. 2011, and Immer et al. 2012, purple circles
representing the 70$\mu$m point sources cataloged by Molinari et al. 2016, and
darker blue circles representing the point sources identified by Gutermuth &
Heyer 2015. The radial size of these circles corresponds to the FWHM condition
used to determine plausible association with nearby CMZoom leaves. Figure 22:
Region 31, Cloud ID G1.085-0.027. The red colorscale shows the 70$\mu$m
emission map from Herschel (Molinari et al., 2010, 2011). The green colorscale
shows the combined 21 and 24$\mu$m emission from MSX and Spitzer respectively
(Benjamin et al., 2003). The blue colorscale shows the 8$\mu$m map from
Spitzer (Benjamin et al., 2003). Each color is shown in logscale, scaled
between a local 5% and 95% boundary value for each box. Overlaid on the
composite three-color image are white contours representing the CMZoom leaves,
along with cyan circles representing YSO candidates from a compilation of
those identified by Yusef-Zadeh et al. 2009, An et al. 2011, and Immer et al.
2012, purple circles representing the 70$\mu$m point sources cataloged by
Molinari et al. 2016, and darker blue circles representing the point sources
identified by Gutermuth & Heyer 2015. The radial size of these circles
corresponds to the FWHM condition used to determine plausible association with
nearby CMZoom leaves.  Figure 23: Region 14, Cloud ID G0.001-0.058, otherwise
known as the 20 km s-1 Cloud. The red colorscale shows the 70$\mu$m emission
map from Herschel (Molinari et al., 2010, 2011). The green colorscale shows
the combined 21 and 24$\mu$m emission from MSX and Spitzer respectively
(Benjamin et al., 2003). The blue colorscale shows the 8$\mu$m map from
Spitzer (Benjamin et al., 2003). Each color is shown in logscale, scaled
between a local 5% and 95% boundary value for each box. Overlaid on the
composite three-color image are white contours representing the CMZoom leaves,
along with cyan circles representing YSO candidates from a compilation of
those identified by Yusef-Zadeh et al. 2009, An et al. 2011, and Immer et al.
2012, purple circles representing the 70$\mu$m point sources cataloged by
Molinari et al. 2016, and darker blue circles representing the point sources
identified by Gutermuth & Heyer 2015. The radial size of these circles
corresponds to the FWHM condition used to determine plausible association with
nearby CMZoom leaves. Figure 24: Region 15, Cloud ID G359.889-0.093, also
known as the 50 km s-1 Cloud. The red colorscale shows the 70$\mu$m emission
map from Herschel (Molinari et al., 2010, 2011). The green colorscale shows
the combined 21 and 24$\mu$m emission from MSX and Spitzer respectively
(Benjamin et al., 2003). The blue colorscale shows the 8$\mu$m map from
Spitzer (Benjamin et al., 2003). Each color is shown in logscale, scaled
between a local 5% and 95% boundary value for each box. Overlaid on the
composite three-color image are white contours representing the CMZoom leaves,
along with cyan circles representing YSO candidates from a compilation of
those identified by Yusef-Zadeh et al. 2009, An et al. 2011, and Immer et al.
2012, purple circles representing the 70$\mu$m point sources cataloged by
Molinari et al. 2016, and darker blue circles representing the point sources
identified by Gutermuth & Heyer 2015. The radial size of these circles
corresponds to the FWHM condition used to determine plausible association with
nearby CMZoom leaves. Figure 25: Region 16, Cloud ID G359.648-0.133. The red
colorscale shows the 70$\mu$m emission map from Herschel (Molinari et al.,
2010, 2011). The green colorscale shows the combined 21 and 24$\mu$m emission
from MSX and Spitzer respectively (Benjamin et al., 2003). The blue colorscale
shows the 8$\mu$m map from Spitzer (Benjamin et al., 2003). Each color is
shown in logscale, scaled between a local 5% and 95% boundary value for each
box. Overlaid on the composite three-color image are white contours
representing the CMZoom leaves, along with cyan circles representing YSO
candidates from a compilation of those identified by Yusef-Zadeh et al. 2009,
An et al. 2011, and Immer et al. 2012, purple circles representing the
70$\mu$m point sources cataloged by Molinari et al. 2016, and darker blue
circles representing the point sources identified by Gutermuth & Heyer 2015.
The radial size of these circles corresponds to the FWHM condition used to
determine plausible association with nearby CMZoom leaves. Figure 26: Region
17, the remaining portion of Cloud ID G0.619+0.012, part of the region also
known as Sgr B2 SE. The red colorscale shows the 70$\mu$m emission map from
Herschel (Molinari et al., 2010, 2011). The green colorscale shows the
combined 21 and 24$\mu$m emission from MSX and Spitzer respectively (Benjamin
et al., 2003). The blue colorscale shows the 8$\mu$m map from Spitzer
(Benjamin et al., 2003). Each color is shown in logscale, scaled between a
local 5% and 95% boundary value for each box. Overlaid on the composite three-
color image are white contours representing the CMZoom leaves, along with cyan
circles representing YSO candidates from a compilation of those identified by
Yusef-Zadeh et al. 2009, An et al. 2011, and Immer et al. 2012, purple circles
representing the 70$\mu$m point sources cataloged by Molinari et al. 2016, and
darker blue circles representing the point sources identified by Gutermuth &
Heyer 2015. The radial size of these circles corresponds to the FWHM condition
used to determine plausible association with nearby CMZoom leaves. Figure 27:
Region 18, Cloud ID G359.484-0.132, also known as Sgr C. The red colorscale
shows the 70$\mu$m emission map from Herschel (Molinari et al., 2010, 2011).
The green colorscale shows the combined 21 and 24$\mu$m emission from MSX and
Spitzer respectively (Benjamin et al., 2003). The blue colorscale shows the
8$\mu$m map from Spitzer (Benjamin et al., 2003). Each color is shown in
logscale, scaled between a local 5% and 95% boundary value for each box.
Overlaid on the composite three-color image are white contours representing
the CMZoom leaves, along with cyan circles representing YSO candidates from a
compilation of those identified by Yusef-Zadeh et al. 2009, An et al. 2011,
and Immer et al. 2012, purple circles representing the 70$\mu$m point sources
cataloged by Molinari et al. 2016, and darker blue circles representing the
point sources identified by Gutermuth & Heyer 2015. The radial size of these
circles corresponds to the FWHM condition used to determine plausible
association with nearby CMZoom leaves. Figure 28: Region 19, Cloud ID
G0.316-0.201. The red colorscale shows the 70$\mu$m emission map from Herschel
(Molinari et al., 2010, 2011). The green colorscale shows the combined 21 and
24$\mu$m emission from MSX and Spitzer respectively (Benjamin et al., 2003).
The blue colorscale shows the 8$\mu$m map from Spitzer (Benjamin et al.,
2003). Each color is shown in logscale, scaled between a local 5% and 95%
boundary value for each box. Overlaid on the composite three-color image are
white contours representing the CMZoom leaves, along with cyan circles
representing YSO candidates from a compilation of those identified by Yusef-
Zadeh et al. 2009, An et al. 2011, and Immer et al. 2012, purple circles
representing the 70$\mu$m point sources cataloged by Molinari et al. 2016, and
darker blue circles representing the point sources identified by Gutermuth &
Heyer 2015. The radial size of these circles corresponds to the FWHM condition
used to determine plausible association with nearby CMZoom leaves. Figure 29:
Region 20, Cloud ID G0.212-0.001. The red colorscale shows the 70$\mu$m
emission map from Herschel (Molinari et al., 2010, 2011). The green colorscale
shows the combined 21 and 24$\mu$m emission from MSX and Spitzer respectively
(Benjamin et al., 2003). The blue colorscale shows the 8$\mu$m map from
Spitzer (Benjamin et al., 2003). Each color is shown in logscale, scaled
between a local 5% and 95% boundary value for each box. Overlaid on the
composite three-color image are white contours representing the CMZoom leaves,
along with cyan circles representing YSO candidates from a compilation of
those identified by Yusef-Zadeh et al. 2009, An et al. 2011, and Immer et al.
2012, purple circles representing the 70$\mu$m point sources cataloged by
Molinari et al. 2016, and darker blue circles representing the point sources
identified by Gutermuth & Heyer 2015. The radial size of these circles
corresponds to the FWHM condition used to determine plausible association with
nearby CMZoom leaves. Figure 30: Region 21, Cloud ID G359.615-0.243. The red
colorscale shows the 70$\mu$m emission map from Herschel (Molinari et al.,
2010, 2011). The green colorscale shows the combined 21 and 24$\mu$m emission
from MSX and Spitzer respectively (Benjamin et al., 2003). The blue colorscale
shows the 8$\mu$m map from Spitzer (Benjamin et al., 2003). Each color is
shown in logscale, scaled between a local 5% and 95% boundary value for each
box. Overlaid on the composite three-color image are white contours
representing the CMZoom leaves, along with cyan circles representing YSO
candidates from a compilation of those identified by Yusef-Zadeh et al. 2009,
An et al. 2011, and Immer et al. 2012, purple circles representing the
70$\mu$m point sources cataloged by Molinari et al. 2016, and darker blue
circles representing the point sources identified by Gutermuth & Heyer 2015.
The radial size of these circles corresponds to the FWHM condition used to
determine plausible association with nearby CMZoom leaves. Figure 31: Region
22, Cloud ID G1.602+0.018. The red colorscale shows the 70$\mu$m emission map
from Herschel (Molinari et al., 2010, 2011). The green colorscale shows the
combined 21 and 24$\mu$m emission from MSX and Spitzer respectively (Benjamin
et al., 2003). The blue colorscale shows the 8$\mu$m map from Spitzer
(Benjamin et al., 2003). Each color is shown in logscale, scaled between a
local 5% and 95% boundary value for each box. Overlaid on the composite three-
color image are white contours representing the CMZoom leaves, along with cyan
circles representing YSO candidates from a compilation of those identified by
Yusef-Zadeh et al. 2009, An et al. 2011, and Immer et al. 2012, purple circles
representing the 70$\mu$m point sources cataloged by Molinari et al. 2016, and
darker blue circles representing the point sources identified by Gutermuth &
Heyer 2015. The radial size of these circles corresponds to the FWHM condition
used to determine plausible association with nearby CMZoom leaves. Figure 32:
Region 23, Cloud ID G1.651-0.050. The red colorscale shows the 70$\mu$m
emission map from Herschel (Molinari et al., 2010, 2011). The green colorscale
shows the combined 21 and 24$\mu$m emission from MSX and Spitzer respectively
(Benjamin et al., 2003). The blue colorscale shows the 8$\mu$m map from
Spitzer (Benjamin et al., 2003). Each color is shown in logscale, scaled
between a local 5% and 95% boundary value for each box. Overlaid on the
composite three-color image are white contours representing the CMZoom leaves,
along with cyan circles representing YSO candidates from a compilation of
those identified by Yusef-Zadeh et al. 2009, An et al. 2011, and Immer et al.
2012, purple circles representing the 70$\mu$m point sources cataloged by
Molinari et al. 2016, and darker blue circles representing the point sources
identified by Gutermuth & Heyer 2015. The radial size of these circles
corresponds to the FWHM condition used to determine plausible association with
nearby CMZoom leaves. Figure 33: Region 24, Cloud ID G1.670-0.130. The red
colorscale shows the 70$\mu$m emission map from Herschel (Molinari et al.,
2010, 2011). The green colorscale shows the combined 21 and 24$\mu$m emission
from MSX and Spitzer respectively (Benjamin et al., 2003). The blue colorscale
shows the 8$\mu$m map from Spitzer (Benjamin et al., 2003). Each color is
shown in logscale, scaled between a local 5% and 95% boundary value for each
box. Overlaid on the composite three-color image are white contours
representing the CMZoom leaves, along with cyan circles representing YSO
candidates from a compilation of those identified by Yusef-Zadeh et al. 2009,
An et al. 2011, and Immer et al. 2012, purple circles representing the
70$\mu$m point sources cataloged by Molinari et al. 2016, and darker blue
circles representing the point sources identified by Gutermuth & Heyer 2015.
The radial size of these circles corresponds to the FWHM condition used to
determine plausible association with nearby CMZoom leaves. Figure 34: Region
25, Cloud ID G0.359.137+0.031. The red colorscale shows the 70$\mu$m emission
map from Herschel (Molinari et al., 2010, 2011). The green colorscale shows
the combined 21 and 24$\mu$m emission from MSX and Spitzer respectively
(Benjamin et al., 2003). The blue colorscale shows the 8$\mu$m map from
Spitzer (Benjamin et al., 2003). Each color is shown in logscale, scaled
between a local 5% and 95% boundary value for each box. Overlaid on the
composite three-color image are white contours representing the CMZoom leaves,
along with cyan circles representing YSO candidates from a compilation of
those identified by Yusef-Zadeh et al. 2009, An et al. 2011, and Immer et al.
2012, purple circles representing the 70$\mu$m point sources cataloged by
Molinari et al. 2016, and darker blue circles representing the point sources
identified by Gutermuth & Heyer 2015. The radial size of these circles
corresponds to the FWHM condition used to determine plausible association with
nearby CMZoom leaves. Figure 35: Region 26, Cloud ID G0.393-0.034. The red
colorscale shows the 70$\mu$m emission map from Herschel (Molinari et al.,
2010, 2011). The green colorscale shows the combined 21 and 24$\mu$m emission
from MSX and Spitzer respectively (Benjamin et al., 2003). The blue colorscale
shows the 8$\mu$m map from Spitzer (Benjamin et al., 2003). Each color is
shown in logscale, scaled between a local 5% and 95% boundary value for each
box. Overlaid on the composite three-color image are white contours
representing the CMZoom leaves, along with cyan circles representing YSO
candidates from a compilation of those identified by Yusef-Zadeh et al. 2009,
An et al. 2011, and Immer et al. 2012, purple circles representing the
70$\mu$m point sources cataloged by Molinari et al. 2016, and darker blue
circles representing the point sources identified by Gutermuth & Heyer 2015.
The radial size of these circles corresponds to the FWHM condition used to
determine plausible association with nearby CMZoom leaves.  Figure 36: Region
27, Cloud ID G1.683-0.089. The red colorscale shows the 70$\mu$m emission map
from Herschel (Molinari et al., 2010, 2011). The green colorscale shows the
combined 21 and 24$\mu$m emission from MSX and Spitzer respectively (Benjamin
et al., 2003). The blue colorscale shows the 8$\mu$m map from Spitzer
(Benjamin et al., 2003). Each color is shown in logscale, scaled between a
local 5% and 95% boundary value for each box. Overlaid on the composite three-
color image are white contours representing the CMZoom leaves, along with cyan
circles representing YSO candidates from a compilation of those identified by
Yusef-Zadeh et al. 2009, An et al. 2011, and Immer et al. 2012, purple circles
representing the 70$\mu$m point sources cataloged by Molinari et al. 2016, and
darker blue circles representing the point sources identified by Gutermuth &
Heyer 2015. The radial size of these circles corresponds to the FWHM condition
used to determine plausible association with nearby CMZoom leaves. Figure 37:
Region 28, Cloud ID G0.714-0.100. The red colorscale shows the 70$\mu$m
emission map from Herschel (Molinari et al., 2010, 2011). The green colorscale
shows the combined 21 and 24$\mu$m emission from MSX and Spitzer respectively
(Benjamin et al., 2003). The blue colorscale shows the 8$\mu$m map from
Spitzer (Benjamin et al., 2003). Each color is shown in logscale, scaled
between a local 5% and 95% boundary value for each box. Overlaid on the
composite three-color image are white contours representing the CMZoom leaves,
along with cyan circles representing YSO candidates from a compilation of
those identified by Yusef-Zadeh et al. 2009, An et al. 2011, and Immer et al.
2012, purple circles representing the 70$\mu$m point sources cataloged by
Molinari et al. 2016, and darker blue circles representing the point sources
identified by Gutermuth & Heyer 2015. The radial size of these circles
corresponds to the FWHM condition used to determine plausible association with
nearby CMZoom leaves. Figure 38: Region 29, Cloud ID G0.714-0.100. The red
colorscale shows the 70$\mu$m emission map from Herschel (Molinari et al.,
2010, 2011). The green colorscale shows the combined 21 and 24$\mu$m emission
from MSX and Spitzer respectively (Benjamin et al., 2003). The blue colorscale
shows the 8$\mu$m map from Spitzer (Benjamin et al., 2003). Each color is
shown in logscale, scaled between a local 5% and 95% boundary value for each
box. Overlaid on the composite three-color image are white contours
representing the CMZoom leaves, along with cyan circles representing YSO
candidates from a compilation of those identified by Yusef-Zadeh et al. 2009,
An et al. 2011, and Immer et al. 2012, purple circles representing the
70$\mu$m point sources cataloged by Molinari et al. 2016, and darker blue
circles representing the point sources identified by Gutermuth & Heyer 2015.
The radial size of these circles corresponds to the FWHM condition used to
determine plausible association with nearby CMZoom leaves. Figure 39: Region
31, Cloud ID G0.326-0.085, also known as the Sailfish. The red colorscale
shows the 70$\mu$m emission map from Herschel (Molinari et al., 2010, 2011).
The green colorscale shows the combined 21 and 24$\mu$m emission from MSX and
Spitzer respectively (Benjamin et al., 2003). The blue colorscale shows the
8$\mu$m map from Spitzer (Benjamin et al., 2003). Each color is shown in
logscale, scaled between a local 5% and 95% boundary value for each box.
Overlaid on the composite three-color image are white contours representing
the CMZoom leaves, along with cyan circles representing YSO candidates from a
compilation of those identified by Yusef-Zadeh et al. 2009, An et al. 2011,
and Immer et al. 2012, purple circles representing the 70$\mu$m point sources