Abstract
Massive star-forming regions exhibit an extremely rich and diverse chemistry, which in principle provides a wealth of molecular probes, as well as laboratories for interstellar prebiotic chemistry. Since the chemical structure of these sources displays substantial spatial variation among species on small scales (≲104 au), high-angular-resolution observations are needed to connect chemical structures to local environments and inform astrochemical models of massive star formation. To address this, we present ALMA 1.3 mm observations toward OB cluster-forming region G10.6-0.4 (hereafter "G10.6") at a resolution of 014 (700 au). We find highly structured emission from complex organic molecules (COMs) throughout the central 20,000 au, including two hot molecular cores and several shells or filaments. We present spatially resolved maps of rotational temperature and column density for a large sample of COMs and warm gas tracers. These maps reveal a range of gas substructure in both O- and N-bearing species. We identify several spatial correlations that can be explained by existing models for the formation of COMs, including NH2CHO/HNCO and CH3OCHO/CH3OCH3, but also observe unexpected distributions and correlations that suggest that our current understanding of COM formation is far from complete. Importantly, complex chemistry is observed throughout G10.6, rather than being confined to hot cores. The COM composition appears to be different in the cores compared to the more extended structures, which illustrates the importance of high-spatial-resolution observations of molecular gas in elucidating the physical and chemical processes associated with massive star formation.
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1. Introduction
Although high-mass stars (>8 M⊙) play a dominant role in cosmic evolution, chemical enrichment of the interstellar medium (ISM), galaxy formation and evolution, and galactic star formation, a detailed understanding of their formation remains elusive due to their short evolutionary timescales, intrinsic rarity, large distances, and heavy obscuration (Zinnecker & Yorke 2007; Tan et al. 2014; Motte et al. 2018). A further complication arises due to the complex, multicomponent process of forming massive protostars, which substantially alter their surroundings, as they become energetic enough to ionize their natal molecular clouds. This first produces hypercompact (HC) H ii regions of sizes ∼0.01 pc (Kurtz et al. 2000), which then expand to form ultracompact (UC) H ii regions of sizes ∼0.1 pc (Churchwell 2002; Hoare et al. 2007), and ultimately with time, compact H ii regions, before all of the material surrounding the newly formed stars is destroyed or dispersed by powerful stellar winds. During this process, these regions possess an extremely rich and diverse chemistry, as the chemical composition of molecular gas involved in star formation is greatly influenced by the physical changes that occur during the star formation process (van Dishoeck & Blake 1998).
In particular, the elevated temperatures and densities generated from collapsing material lead to the production and destruction of various molecular species and result in a high degree of chemical complexity (Schilke et al. 2001; Bisschop et al. 2007; Belloche et al. 2013), which in turn leads to the emergence of hot molecular cores. These hot cores, which exhibit intense emission in numerous complex organic molecules (COMs), are often associated with hot and dense regions near massive young stellar objects (MYSOs). However, the complex chemical and physical processes driving these regions are not fully understood, despite decades of observations (Blake et al. 1987; Gibb et al. 2000) and modeling efforts (Charnley et al. 1992, 1995a, 1995b; Garrod & Herbst 2006; Garrod et al. 2008; Laas et al. 2011; Choudhury et al. 2015). For instance, the presence of externally heated hot cores located in the vicinity of UC H ii regions (Wyrowski et al. 1999; De Buizer et al. 2003; Mookerjea et al. 2007) has challenged the notion that hot cores are simply a stage in the evolutionary sequence of massive protostars. In reality, hot cores may also originate as chemical manifestations of UC H ii regions on their environments, rather than simply being precursors to UC H ii regions, and be driven, in part, by COM production from ice photochemistry due to abundant UV and X-ray photons (Öberg 2016).
Numerous studies at low spatial resolution confirmed the presence of a COM-rich chemistry in MYSOs (e.g., Turner 1991; Schilke et al. 1997; Tercero et al. 2010), while those conducted at higher resolution revealed that this chemistry is highly structured on small scales (≲104 au) (e.g., Beuther et al. 2005; Mookerjea et al. 2007; Qin et al. 2010; Guzmán et al. 2018; Moscadelli et al. 2018; Bøgelund et al. 2019; Gieser et al. 2019; Molet et al. 2019). Such observations, which directly resolve the spatial differences between the emission of distinct species, allow us to unambiguously discern the regions traced by different molecular species and families of molecules, providing further insight into their formation processes and chemistry. As a result, they are crucial for constraining a variety of outstanding questions related to the chemical evolution of MYSOs: How frequently and in what way are hot cores associated with UC H ii regions (e.g., Mookerjea et al. 2007; Lindberg et al. 2017)? What processes and evolutionary stages are responsible for COM production in massive star-forming regions (e.g., Garrod et al. 2017; El-Abd et al. 2019)? Are there several distinct COM chemistries that can be used to trace different aspects of star formation (e.g., Fontani et al. 2007; Suzuki et al. 2018; Tercero et al. 2018)? Are O- and N-bearing COMs systematically spatially offset from one another (e.g., Blake et al. 1987; Wyrowski et al. 1999; Qin et al. 2010; Jiménez-Serra et al. 2012)?
To address these questions, we investigated the small-scale spatial structure of a representative set of COMs in the well-known massive star-forming region G10.6-0.4 (hereafter "G10.6"). G10.6 is a ∼106 L⊙ OB cluster-forming region (Casoli et al. 1986; Lin et al. 2016) at a distance of 4.95 kpc (Sanna et al. 2014b). Unresolved observations with the Submillimeter Array (SMA) revealed that the dense gas surrounding its central proto-OB-cluster is particularly COM- and hydrocarbon-rich (Jiang et al. 2015; Wong & An 2018). Hints of chemical substructure were seen in ∼1'' resolution SMA observations of a sample of shock tracer molecules, especially in Eu ≈ 100–150 K lines of SO2 and OCS (Liu et al. 2010b). These observations suggested a rich, spatially variable complex chemistry taking place in the central 3'' (∼0.09 pc).
In this paper, we present a detailed study of the complex chemistry toward the central 20,000 au of G10.6 using Atacama Large Millimeter/submillimeter Array (ALMA) Band 6 observations at 014. In Section 2, we describe the observations and data reduction. In Section 3, we discuss the methods for extracting the physical conditions of spatially resolved gas and show a detailed example for CH3OH. We present maps of rotational temperature and column density, as well as spatial correlations for all molecules in our sample in Section 4. We discuss the COM chemistry of G10.6 and compare it with other well-studied regions in Section 5, and summarize our conclusions in Section 6.
2. Observations
2.1. Observational Details
G10.6 was observed on 2016 September 9–10 and 2017 July 19 in Band 6 as part of the ALMA Cycle 5 project 2015.1.00106.S. The first execution block included 36 antennas with projected baseline lengths between 15 and 3144 m (11–2462 k
The phase center of both observations was located at R.A. (J2000) = 18h10m28683, decl. (J2000) = −19°55'4907. The FWHM of the ALMA primary beam was 251, and as a result primary beam corrections were not necessary. For both executions, the quasar J1924-2914 was used for bandpass calibration and J1832-2039 was used for phase calibration, while J1733-1304 served as the flux calibrator. We assume a 10% flux calibration uncertainty.
2.2. Data Reduction, Continuum Subtraction, and Imaging
Initial data calibration was performed by ALMA/NAASC staff. The reduction of the first execution used CASA version 4.7.0, while the reduction of the second execution and all subsequent imaging used CASA version 4.7.2 (McMullin et al. 2007). The data cubes were imaged using the tclean task with a Briggs robust weighting parameter of 0.5 to achieve a compromise between resolution and sensitivity to extended emission. The resulting images have a square pixel size of 0018 and an overall size of ∼43'', which is approximately twice the primary beam FWHM at 1.3 mm. We then trimmed these images to the innermost 9'' by 7'' region, which is known to contain the densest gas and hence the most complex and varied chemistry (e.g., Liu et al. 2010b).
Due to the high sensitivity and dynamic range of the observations, no sufficiently "line-free" channels exist across the entirety of the map, especially toward regions containing the densest gas. As a result, we were unable to subtract the continuum emission in the Fourier domain and instead performed the continuum subtraction in the image plane. We followed the procedures of Jørgensen et al. (2016) to define the continuum in a homogeneous and automated way based on the density distribution of channel intensities in each pixel. In brief, the flux density distribution of each pixel was first fit with a symmetric Gaussian. Then, the centroid of this fit was used to define a fitting range for a skewed Gaussian fit and the new centroid value (no longer necessarily symmetric) was recorded as the continuum level for that particular pixel. For pixels with only continuum contribution and no line emission, the distribution is a symmetric Gaussian centered at the continuum level with a width corresponding to the rms noise
We derived the continuum rms for each spectral window as the median value of all pixels without significant continuum emission. To do so, we excluded the central 0.06 pc region of G10.6, which possesses highly structured continuum emission, and point-source-like emission associated with an independent UC H ii region located to the west. The derived continuum rms was then used to derive rms per spectral bin. Overall, we found a typical continuum rms of ∼0.60–0.65 mJy beam−1 (∼0.79–0.87 K) with a synthesized beam size of 014, which corresponds to an approximate physical scale of 700 au at the distance of G10.6. A summary of beam sizes and rms values per spectral window is shown in Table 1. Fully reduced spectral cubes are publicly available on Zenodo doi: 10.5281/zenodo.4454165.
Table 1. Overview of Spectral Windows
Frequency Range | Beam Size | Position Angle | rms | |
---|---|---|---|---|
(GHz) | (arcsec × arcsec) | (deg) | (mJy beam−1) | (K) |
216.948–218.823 | 0.15 × 0.13 | 118 | 0.60 | 0.79 |
219.053–220.928 | 0.15 × 0.13 | 110 | 0.65 | 0.84 |
231.054–232.929 | 0.14 × 0.12 | 115 | 0.63 | 0.85 |
232.949–234.824 | 0.14 × 0.12 | 120 | 0.65 | 0.87 |
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2.3. Overview of G10.6
G10.6 is a well-suited target for a study of complex chemistry at high spatial resolution. Several H ii and UC H ii regions are present across the central ∼10 pc area, which suggests that massive star formation is simultaneously occurring over the entire molecular cloud (Ho & Haschick 1986; Sollins & Ho 2005). G10.6 exhibits a centrally concentrated distribution of gas (Lin et al. 2016) with several approximately radially aligned, 5–10 pc dense gas filaments, which connect to a central ∼1 pc scale massive molecular clump (Liu et al. 2012; Liu 2017). Higher-angular-resolution observations of dense molecular gas tracers revealed that some of these large-scale filaments are converging to a rotating, ∼0.6 pc scale massive molecular envelope (Omodaka et al. 1992; Ho et al. 1994; Klaassen et al. 2009; Liu et al. 2010a, 2010b, 2011). The massive proto-OB stars and associated UC H ii region (Ho et al. 1986; Sollins et al. 2005) are deeply embedded in this rotationally flattened (Keto et al. 1987, 1988; Guilloteau et al. 1988) envelope, where low-density gas around the rotational axis has been either photoionized or dispersed by expanding ionized gas (Liu et al. 2010a, 2011). High-excitation (Eu ≳ 100 K) molecular lines trace a ∼0.1 pc "hot toroid" at the center of this massive molecular envelope (Liu et al. 2010a; Beltrán et al. 2011), which hosts the luminous proto-OB cluster. Very Large Array (VLA) observations of NH3 (3,3) satellite hyperfine line absorption at 01 showed that the dense gas comprising the hot toroid is extremely clumpy (Sollins & Ho 2005). Overall, the geometric configuration of the central ∼1 pc scale massive molecular clump resembles that of a scaled-up version of a low-mass star-forming core and disk system viewed edge-on. For a more detailed, multiscale view of G10.6 and its environment, see Liu (2017).
2.4. Observed Small-scale Structure of G10.6
To better contextualize COM emission in the central region of G10.6, it is beneficial to first understand the broader physical conditions and gas structures as revealed by the continuum emission and distribution of ionized gas as shown in Figure 1. For consistency, we adopt the same nomenclature used in Sollins et al. (2005) and denote prominent features as A1–A6, B1–B5, C1–C2, and D. Features labeled as A correspond to localized arcs of ionized gas, and those marked as B are associated with a central cavity evacuated by a wide-angle outflow, as traced by strongly emitted ionized gas. In particular, B1, B3, and B4 define the southwest edges of this outflow, while B2 and B5 mark the northeast edges. B5 is also the location of an elongated ridge containing the brightest H30
Although more spatially extended, the ionized gas largely traces the continuum emission, as expected, since the majority of the millimeter continuum originates from free–free emission (Liu et al. 2010b). However, we see a local maximum in continuum emission toward both HC1 and C2, but do not observe similar peaks in the H30
3. Data Analysis
3.1. Molecule Sample
The ALMA observations of G10.6 cover a wide bandwidth, which provides coverage of numerous rotational transitions of many molecular species. We selected a chemically representative set of COMs commonly observed toward massive star-forming regions. These molecules are: CH3OH, CH3OCH3, CH3OCHO, CH3CHO, NH2CHO, CH3CH2CN, CH2CHCN, CH3CN, and HNCO. We also included the isotopologues 13CH3CN, , and 13CH3OH, which not only provide valuable information about isotopic abundances in G10.6, but also trace denser and more optically thin gas relative to their main species. Each species had a sufficient number of lines to robustly derive rotational and column densities via a population diagram method over a wide spatial area in G10.6. Table 2 summarizes the number of identified lines, range of upper-state energies, and Einstein A coefficients covered by these lines. An example of the analysis process is shown for CH3OH in the following subsections.
Table 2. Summary of Targeted Species
Species | Name | Nlines a | Eu | Aul | Catalog | Fitting Threshold b | |
---|---|---|---|---|---|---|---|
(K) | (10−5 s−1) | Nlines | |||||
CH3OH | Methanol | 10 | 46–802 | 2.04–4.69 | CDMS | 3 | 51 |
13CH3OH | 5 | 48–594 | 1.30–5.27 | CDMS | 3 | 206 | |
CH3OCH3 | Dimethyl ether | 7 | 81–673 | 1.44–9.14 | CDMS | 3 | 57 |
CH3OCHO | Methyl formate | 31 | 100–282 | 3.42–18.39 | JPL | 5 | 100 |
CH3CHO | Acetaldehyde | 11 | 82–183 | 28.84–44.45 | JPL | 4 | 50 |
NH2CHO | Formamide | 10 | 61–175 | 74.75–147.23 | CDMS | 9 | 114 |
CH3CN | Methyl cyanide | 11 | 69–931 | 10.10–63.71 | JPL | 7 | 257 |
13CH3CN | 10 | 78–942 | 30.45–107.96 | JPL | 8 | 350 | |
8 | 69–419 | 60.71–92.31 | JPL | 6 | 179 | ||
CH3CH2CN | Ethyl cyanide | 31 | 33–837 | 3.04–105.49 | CDMS | 18 | 172 |
CH2CHCN | Vinyl cyanide | 12 | 135–435 | 216.94–321.65 | CDMS | 5 | 25 |
HNCO | Isocyanic acid | 10 | 58–1050 | 6.68–24.02 | CDMS | 3 | 170 |
Notes.
a Combined multiplets are counted as one line and we only consider unblended lines. b This empirical threshold corresponds to the minimum number of unblended lines and range in Eu values that we required to be present in each pixel for a fit to be attempted. Such cutoffs were employed to ensure that all reported determinations of rotational temperature and column density were robust.Download table as: ASCIITypeset image
To illustrate the chemical and physical diversity across G10.6, Figure 2 shows integrated intensity maps for representative lines with comparable excitation conditions (Eu ≈ 100 K) from each COM in our sample. We also extracted spectra from representative positions labeled in Figures 1 and 2. Spectra covering half of the observed bandwidth are shown in Figure 3, while the other half are shown in Figure 20 in Appendix A. Key lines are labeled, but we did not attempt a detailed identification of all lines within the spectral coverage and instead focus on those originating from the selected COMs. A high degree of variation in line strength, width, and richness is evident. Some COMs, e.g., NH2CHO and CH2CHCN, are seen primarily toward HC1, while others, such as CH3CN and CH3OH, are observed in almost all positions, albeit at varying intensity levels.
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Standard image High-resolution image3.2. Fitting Process
For each species in the selected COM sample, we identified and fit all unblended transitions with single Gaussian profiles. All lines belonging to a single species were fit consistently. Blended lines were removed via visual inspection, while line assignments were checked by verifying that the best-fit model for each species did not predict lines at frequencies, covered by our observations, where no emission is detected.
In order to verify the spatial consistency of the spectral fits, we also visually inspected maps of integrated intensity, systemic velocity, and line FWHM for each transition included in our analysis. In all cases, we found a reasonably coherent and smoothly varying morphology throughout G10.6 (see Appendix B). We also confirmed that, in each case, the distributions of velocity and line FWHM values were not sharply peaked toward either the minimum or maximum limits designated in the fitting code. A representative set of maps are shown in Figure 4 for CH3OH.
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Standard image High-resolution imageWe then constructed maps of rotational temperature and column density for each COM species using a rotational diagram analysis (e.g., Goldsmith & Langer 1999) on a pixel-by-pixel basis. To ensure secure determinations of rotational temperature and column density across a large spatial extent in G10.6, we restricted our fittings to those pixels with a sufficient number of lines with a wide coverage of Eu, as shown in Table 2.
We used the Markov Chain Monte Carlo (MCMC) code emcee (Foreman-Mackey et al. 2013) to generate posterior probability distributions of column densities and rotational temperatures consistent with the observed data. Random draws from these posteriors are plotted in purple for several positions toward G10.6 in Figure 5 with
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Standard image High-resolution imageIn general, we initially explored a parameter space from 1014 cm−2 ≤ Ecol ≤ 1020 cm−2 and 10 K ≤ Trot ≤ 800 K, based on physical gas conditions expected in massive star-forming regions (Bisschop et al. 2007; Suzuki et al. 2018; Molet et al. 2019). After this first model run, we ran a second iteration with narrower, species-specific grids and then performed quality checks to ensure that the fitted Trot and Ecol values were not sharply peaked at the extremes of our priors. For each line and species, we also visually inspected the fitted
The resultant maps of rotational temperature and column density derived for CH3OH are shown in Figure 6. As a result of this MCMC fitting process, we also derived formal uncertainties on temperature and column density, which were found to be small toward the central region of G10.6, but became large toward the edges of the map. This is not unexpected as we detect fewer high Eu lines toward the edges of the map, and the lines that we do detect decrease in intensity relative to those toward the central region of G10.6, which increases the Gaussian fitting errors. A similar trend was found in all of the molecules in our sample, and in no cases did we observe large spatial regions of unexpectedly high uncertainties. In addition to the initial quality cuts shown in Table 2, we also excluded pixels with particularly high uncertainties (>200%) and those with highly discontinuous and outlier values. Thus, the lack of a model result for a specific pixel does not necessarily imply the absence of molecular emission, as is clearly seen when comparing integrated line intensities and maps of column density for several species.
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Standard image High-resolution imageMaps of column density and rotational temperature were derived using the method above with no modifications for six out of nine species in our sample. However, three molecules warranted special treatment: CH3OCHO, CH3CH2CN, and CH3CN. We ware unable to derive independent rotational temperatures for CH3OCHO, which exhibited unusually large scatter in its rotational diagrams, and instead adopted those of the chemically similar molecule CH3OH (e.g., Garrod & Herbst 2006; Garrod et al. 2008) to derive column density. A two-component rotational diagram was required to fit the majority of CH3CH2CN emission, and regions of optically thick CH3CN emission required the use of the optically thin isotope . These latter two cases are discussed in more detail in the following two subsections.
3.3. Two CH3CH2CN Temperature Components
All line data were further analyzed to explore whether the data were better fit by two distinct temperature components rather than a single component. A two-component fit was only favored for CH3CH2CN, in which we clearly identified two separate temperature components throughout most of G10.6, as show in Figure 7. Wherever two components were needed, most of the column density is carried by the colder component, which we therefore designate as the primary component. To not overfit the data, we restricted this two-component analysis to instances where the secondary component had a rotational temperature that was 1.5× in excess of that of the primary component. Otherwise, we fit that pixel with a single rotational temperature. We defined the total column density of CH3CH2CN as the sum of both components and used the total column density for all subsequent analysis. Previous indications of multiple CH3CH2CN temperature components were seen toward Orion KL by Daly et al. (2013), who also observed a similar transition between different components at Eu ≈ 150–200 K.
3.4. Optically Thick CH3CN and Isotopologues
Initial efforts to fit the central regions of CH3CN revealed optically thick gas, as indicated by poor fittings and unphysical temperatures (Trot ≳ 1000 K). High line optical depths (
To derive this factor, we determined the 12C/13C ratio from the column density ratios of CH3OH/13CH3OH. A detailed discussion of this process is provided in Appendix D. Overall, we find a median column density ratio of 22.8, which is the value we adopt. This is a factor of two lower than the expected ratio of 43 (Milam et al. 2005) at the distance of G10.6 (DGC = 3.9 kpc), but similar low values of 12C/13C have been derived in COMs at core scales in star-forming regions, e.g., hot corinos (Jørgensen et al. 2016) and hot cores (Sanna et al. 2014a; Beltrán et al. 2018; Bøgelund et al. 2019). However, the carbon isotopic ratio in G10.6 needs to be revisited with more comprehensive isotopologue data, and as a result the reported CH3CN column densities in high-density regions should only be considered accurate within a factor of 2.
4. Results
4.1. CH3OH Substructure
COMs exhibit complex emission morphologies and substantial gas substructures across G10.6. As shown in Figure 6, this is well illustrated by the maps of rotational temperature and column density of CH3OH, the most spatially extended maps in our sample. When appropriate, we refer to COM features, namely B3–B5, C1, and HC1–HC2, using the nomenclature introduced above. For instance, hot cores HC1 and HC2 are clearly identified by their compact, high column densities and elevated temperatures. The south cavity edge (B3) contains a spatially extended region of hot, high-density gas, while the northeast cavity edge (B5) exhibits the hottest gas (≳400 K) anywhere in G10.6 and possesses a relative deficit of molecular gas. Since B5 is also the location of an ionized ridge of material containing the brightest H30
Newly identified gas substructures that have no obvious correspondence to the features of Sollins et al. (2005) are labeled as E, F1–F4, and MR. Feature E denotes a clump of gas within the central cavity of G10.6 and is bounded by the cavity edges B3 and B5. Four separate filamentary structures are marked as F. F1 is a tri-pronged structure on the eastern edge of G10.6, while F2 comprises a single narrow filament extending beyond B3. The F3 filament lies directly to the north of HC1 and may be related to hot-core activity or may be simply a further extension of the "V"-shaped F4 filament located to the north of the MR. An elongated and somewhat irregular "Z"-shaped structure is seen immediately to the north of B5. As it is readily identified by a band of high-density gas, we thus refer to this structure as the "molecular ridge," denoting it as MR. The shape of the MR suggests that it is interacting with the ionized gas in B5, and its relative molecular richness (e.g., Figure 3) and high column density may be attributed to external heating from B5. The western portion of the MR appears to be marginally resolved into a core-like structure, which is tentatively labeled as HC3.
4.2. Rotational Temperatures and Column Densities
Spatially resolved maps of rotational temperature and column density for all molecules in our sample are shown in Figures 8 and 9, respectively. In terms of spatial coverage, NH2CHO and CH2CHCN are the most limited, CH3OH and CH3CN are the most extended, and the remaining species have intermediate spatial distributions. HC1 is prominent in all species, exhibiting elevated rotational temperatures and high column densities. HC2 is also seen in all column density maps, but is less enhanced in rotational temperature (except for HNCO). The MR and B3 also consistently exhibit high column densities in the majority of COMs. Filamentary features are seen in most molecules, although with varying extents and column densities. For instance, CH3OCH3 and CH3OCHO show narrow features, e.g., F1 and F4, while CH3CN is the only species with extended substructure comparable to that of CH3OH. Interestingly, HC3 is consistently marginally resolved (e.g., CH3OCHO, CH3CN, CH3CH2CN), indicating the potential presence of high-density clumps/cores that are unresolved in our observations.
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Standard image High-resolution imageThe rotational temperature maps reveal that there is no single temperature that characterizes all COMs at a specific location. Differences in temperatures span hundreds of kelvin, indicating that multiple environments are traced along the line of sight in this complex region. On average, CH3CHO exhibits the lowest rotational temperatures (≲60 K), while NH2CHO and CH2CHCN have moderate temperatures (∼70–150 K). CH3CN, CH3OH, CH3OCH3, CH3CH2CN, and HNCO all possess substantially higher temperatures (∼150–400 K).
Within the N-bearing COM family, we notice prominent differences between the spatial distributions of complex cyanides (CH3CN, CH3CH2CN, CH2CHCN) and HNCO. HNCO also displays a different temperature pattern, including a dual-peaked hot core 1 (HC1–D), a prominent HC2, and curved bands of elevated temperatures, which are marked as G in Figure 8. Together, these distinct patterns of column density and temperature suggest that there is no single N-bearing COM chemistry and that the amount of nitrogen incorporated into different kinds of organics depends strongly on the local environment.
Among O-bearing species, CH3OH, CH3OCH3, and CH3OCHO each trace different structures in G10.6. CH3OH is widely distributed throughout G10.6, as described in Section 4.1, while CH3OCHO exhibits a significant enhancement in HC1 and shares broad morphological similarities with CH3CHO, notwithstanding its increased uncertainties as reflected in a less uniform column density map. CH3OCH3 has an inverted "C"-shaped distribution of hot, clumpy gas (labeled as G) that connects the western edge of the MR to B3 and presents its highest column density in the MR rather than in HC1. This distribution of temperature and column density is not seen in any other molecule in our sample, and may reflect the fact that CH3OCH3 is responding differently to strong radiation fields from nearby B5 than the other O-bearing COMs. By contrast, CH3OH only shows weak enhancements along the MR, and CH3OCHO shows none at all. Notably, the CH3OCH3 and CH3OCHO maps appear strikingly different, which is somewhat surprising considering that all proposed chemical formation routes (e.g., Garrod & Herbst 2006) indicate that they are directly linked.
In Table 3, we provide a list of rotational temperatures and column densities toward four regions of particular interest: HC1–HC2, B3, and MR. Figure 10 presents a summary of derived column densities toward these same positions. Variations in column density between species span three orders of magnitude at each position, with CH3OH being most abundant at all locations. HC1, HC2, and B3 appear broadly similar in their chemical compositions, as indicated by a similar distribution of COM abundances with respect to CH3OH. However, HC1 exhibits at least an order-of-magnitude enhancement in CH3OCHO relative to the other positions, while B3 is deficient in NH2CHO and the MR is deficient in both NH2CHO and CH2CHCN.
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Standard image High-resolution imageTable 3. COM Rotational Temperatures and Column Densities at Regions of Interest in G10.6
Trot | NX | Trot | NX | ||||
---|---|---|---|---|---|---|---|
(K) | (1016 cm−2) | (%) | (K) | (1016 cm−2) | (%) | ||
Hot Core 1 (HC1) | Hot Core 2 (HC2) | ||||||
CH3OH | 100 | CH3OH | 100 | ||||
CH3OCH3 | 0.75 | CH3OCH3 | 1.2 | ||||
CH3OCHO | 35 | CH3OCHO | 4.0 | ||||
CH3CHO | 0.054 | CH3CHO | 0.21 | ||||
NH2CHO | 0.57 | NH2CHO | 0.42 | ||||
CH3CN | 2.0 | CH3CN | 1.2 | ||||
0.088 | 0.054 | ||||||
CH3CH2CN: | ⋯ | 1.1 | CH3CH2CN: | ⋯ | 1.0 | ||
Primary | 0.82 | Primary | 0.67 | ||||
Secondary | 0.30 | Secondary | 0.33 | ||||
CH2CHCN | 0.84 | CH2CHCN | 0.25 | ||||
HNCO | 1.9 | HNCO | 0.90 | ||||
S Cavity Edge (B3) | Molecular Ridge (MR) | ||||||
CH3OH | 100 | CH3OH | 100 | ||||
CH3OCH3 | 2.6 | CH3OCH3 | 2.7 | ||||
CH3OCHO | 5.9 | CH3OCHO | 1.6 | ||||
CH3CHO | 0.080 | CH3CHO | 0.078 | ||||
NH2CHO | <0.0102 | <0.0038 | NH2CHO | <0.0101 | <0.0030 | ||
CH3CN | 1.8 | CH3CN | 0.74 | ||||
0.077 | 0.033 | ||||||
CH3CH2CN: | ⋯ | 1.1 | CH3CH2CN: | ⋯ | 0.79 | ||
Primary | 0.80 | Primary | 0.65 | ||||
Secondary | 0.27 | Secondary | 0.13 | ||||
CH2CHCN | 0.36 | CH2CHCN | <0.0138 | <0.0041 | |||
HNCO | 0.43 | HNCO | 0.047 |
Note. Uncertainties at the 1
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4.3. Spatial Column Density Correlations
To accurately compare spatial trends of different species, we first performed 1/4-beam sampling, i.e., four data points extracted for each beam area, on a consistent spatial grid that was then applied uniformly to all COMs in the sample and used for all subsequent correlation analysis. We did not attempt to derive fractional abundances with respect to hydrogen due to a lack of H2 gas tracers on these scales; we cannot, for example, distinguish the free–free and dust contributions to the overall continuum emission. We instead compared column densities using the cross-correlation between each pair of molecules according to Guzmán et al. (2018) via
Sums were taken over each quarter-beam position with I1,ij
and I2,ij
corresponding to the values at each position i, j and the weight wij
is equal to either 0 or 1 if a column density was able to be determined for that position or not. By definition,
The left panel of Figure 11 shows the calculated cross-correlations for all pairs of molecules, excluding CH2CHCN, which lacked a sufficient number of independent data points for meaningful comparison. Although spatially compact, the column density map of NH2CHO still covers nearly 20 independent beams and thus we chose to include it in this analysis. We find strong correlations between: NH2CHO/HNCO and NH2CHO/CH3OCHO, which are dominated by HC1 and HC2; CH3CN/CH3CH2CN and CH3OH/CH3OCH3, which are expected to be chemically related and trace similar column density structures; and CH3OH/CH3CN, which are the two most extended molecules and likely probe total gas column densities. We also note that correlations between the saturated cyanides CH3CH2CN and CH3CN are greater than those between pairs of saturated and unsaturated N-bearing species, such as CH3CN/NH2CHO, CH3CH2CN/NH2CHO, or CH3CH2CN/HNCO. The weakest correlations are typically found between CH3OCH3 and molecules such as HNCO, NH2CHO, and CH3OCHO, which reflects the unique column density distribution of CH3OCH3.
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Standard image High-resolution imageAs noted by Guzmán et al. (2018), sections of an image with a higher column density weigh more into the calculation of
As expected, correlations between NH2CHO and HNCO and other species dramatically decrease, since these molecules are most prominently detected toward HC1. We do note, however, the caveat that only ∼10 independent beams are available for correlations involving NH2CHO, which is a reduction of 50% after excluding HC1. Cross-correlations involving the spatially extended molecules CH3OH and CH3CN are roughly the same. CH3OCH3, despite its unique column density distribution, remains strongly correlated with CH3OH irrespective of the inclusion or exclusion of HC1. We find that CH3OCHO is now well correlated with the other O-bearing COMs CH3OH and CH3OCH3. This suggests that outside of HC1 these molecules co-form and that the hot-core environment acts to specifically enhance or destroy some COMs that are otherwise chemically related.
While cross-correlations are informative of general chemical relatedness, they do not capture the fact that multiple trends within single molecular pairs may exist in G10.6. To investigate the existence of such correlations directly, we show correlation plots for each pair of molecules in Figure 12. We labeled the percentage overlap between the two molecules being compared in the upper left corner of each panel, which helps inform the spatial extent over which these trends can be reliably interpreted. We defined this percentage overlap as the fraction of pixels from the species with a smaller spatial extent relative to the fraction of pixels from the species with a larger spatial extent. For instance, the 54% overlap between CH3OH and CH3CN means that out of all the CH3OH pixels with determinations of Trot and Ecol, only 54% of the corresponding pixels have derivations of Trot and Ecol for CH3CN.
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Standard image High-resolution imageThe majority of species have positive trends, but are not well described by a single relation and instead exhibit complex trends with multiple components. One notable exception to this trend is CH3CHO, which is largely uncorrelated with all other species. To leverage the additional information provided by rotational temperatures, we also color-coded the scatter points by temperature. Two distinct high-temperature components are frequently observed: one that can be attributed to HC1, where the highest column densities and high temperatures are typically observed, and a second from B5, which hosts the strongest H30
While strong correlations are observed for numerous species, such as NH2CHO and CH2CHCN, we caution against a broad interpretation of these trends. As reflected in the small percentage (≲10%) of mutual pixels, these trends are only applicable toward the densest regions of gas, namely HC1 and HC2. A good example of this is the correlation between CH2CHCN/HNCO, which is the tightest correlation observed but has only a 7% pixel overlap. This indicates that such a correlation is applicable to a minimally shared region between HNCO and CH2CHCN, which in this case is HC1, HC2, and a few small patches of gas toward B3. However, some strongly correlated molecules show a single component with large overlap, such as CH3OH and CH3CN, which indicates co-formation across a wide range of environments.
4.4. Rotational Temperature versus Column Density
Next, we investigated the relationship between rotational temperature and column density in each species in Figure 13. Temperature and density trends within a single species not only help characterize the gas excitation conditions present in G10.6, but can also reveal the presence of additional chemical formation and destruction pathways.
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Standard image High-resolution imageAlthough most species display a positive relation between Trot and Ecol, there is a large range in the relative strength of this association. In general, a large fraction of the gas in N-bearing species, such as CH3CN, is relatively insensitive to rotational temperature, while the column densities of O-bearing species, such as CH3OH and CH3OCHO, are highly correlated with gas temperature. However, this trend is less clear for CH3OCH3 and further illustrates its distinct temperature and column density distributions. CH3CHO and, to a lesser degree, NH2CHO display negative associations with temperature and are notable outliers to this overall positive Trot–Ncol trend.
To assess spatially dependent trends, regions of interest were color-coded in Figure 13. HC1 exhibits a distinct and tightly positive correlation between temperature and column density for all species, except for CH3CHO and CH3OCH3. The diffuse correlation seen in CH3CHO is due to its noisier column density map and likely does not reflect true gas conditions. For CH3OCH3, HC1 still exhibits a relatively tight Trot–Ncol association but the largest column densities are instead found in the molecular ridge. The existence of two well-defined HNCO trends in HC1 arises from the complex, dual-peaked temperature structure seen in Figure 8.
HC2 and B3 span a range of different Trot–Ncol associations, from extremely diffuse correlations (CH3CN, HNCO) to tight positive relations (CH3OH, CH3OCHO) and even negative trends (CH3CHO, NH2CHO). No clear trends were identified among different types of molecules for either region. Although not labeled in Figure 13, a diffuse component of high rotational temperature but gas of modest column density is seen in several species, such as CH3OH, CH3OCH3, CH3CN, and HNCO, and corresponds to B5.
5. Discussion
5.1. Spatial Distribution of N- versus O-bearing Species
Spatial separations between N- and O-bearing COMs have been observed toward several high-mass star-forming regions, such as Orion (Blake et al. 1987; Wright et al. 1996; Beuther et al. 2005; Feng et al. 2015), W3(OH)/W3(H2O) (Wyrowski et al. 1999), G19.61-0.23 (Qin et al. 2010), and AFGL 2591 (Jiménez-Serra et al. 2012). However, efforts to assess the ubiquity of such separations with single-dish surveys have so far proved inconclusive (Fontani et al. 2007; Suzuki et al. 2018), but rather require interferometric observations, which can resolve small-scale chemical variations to identify and explain such spatial trends (e.g., Tercero et al. 2018; El-Abd et al. 2019). Here, we aim to test whether chemical differentiation is seen on small scales throughout G10.6 and investigate observed COM spatial trends.
Although we find no evidence for systematic small-scale separations between N- and O-bearing COMs in G10.6, we identify several correlations within and between these molecular families. The observed spatial correlations among the O-bearing species CH3OH, CH3OCH3, and CH3OCHO probably reflect intrinsic chemical similarity and related formation pathways (see Table 4), and have been previously seen in several MYSOs (e.g., Bisschop et al. 2007; Brouillet et al. 2013). We also find a strong spatial correlation between the nitriles CH3CN and CH3CH2CN. Together with their high column densities, this likely implies a formation route via grain surfaces (e.g., Mookerjea et al. 2007). Previous models have suggested grain surface hydrogenation and evaporation of accreted CH3CN and HC3N to form CH3CH2CN (Charnley et al. 1992; Caselli et al. 1993), but based on studies reporting nitrile predictions, these pathways underproduced CH3CN and CH3CH2CN abundances (Caselli et al. 1993; Millar et al. 1997). These small-scale observations strongly suggest that, however complex nitriles form, the formation pathways of medium and large nitriles are linked.
Table 4. Chemical Pathways of Interest
COM | Number | Pathway | Type | References |
---|---|---|---|---|
CH3OCHO | [1] | O + CH3OCH2 → CH3OCHO + H | Cold gas | 1 |
[2] | CH3O + HCO → CH3OCHO | Ice surface | 2, 3 | |
[3] | CH3OH + HCOOH → CH3OCHO | Warm gas | 4 | |
CH3OCH3 | [4] | CH3O + CH3 → CH3OCH3 + photon | Cold gas | 1 |
[5] | CH3O + CH3 → CH3OCH3 | Ice surface | 5 | |
[6] | CH3OH + CH3OH → CH3OCH3 | Warm gas | 6 | |
NH2CHO | [7] | HNCO + H + H → NH2CHO | Ice surface | 7 |
[8] | NH2 + HCO → NH2CHO | Ice surface | 8, 9 | |
[9] | NH3 + CO → NH2CHO | Ice surface | 8, 10 | |
[10] | H2CO + NH2 → NH2CHO + H | Warm gas | 11, 12 | |
CH3CHO | [11] | CH3 + HCO → CH3CHO | Ice surface | 13 |
[12] | CH3CH2 + O → CH3CHO + H | Warm gas | 14 |
References. (1) Balucani et al. (2015), (2) Garrod et al. (2008), (3) Laas et al. (2011), (4) Neill et al. (2011), (5) Öberg et al. (2010), (6) Charnley et al. (1995a), (7) Charnley (1997), (8) Jones et al. (2011), (9) Fedoseev et al. (2016); (10) Rimola et al. (2018), (11) Kahane et al. (2013), (12) Barone et al. (2015), (13) Garrod & Herbst (2006), (14) Charnley (2004).
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CH3OH and CH3CN, the most spatially extended O- and N-bearing species, respectively, in our sample, possess similar spatial distributions and tight column density correlations across G10.6. This is surprising because prior observations of MYSOs have reported a lack of correlation between these species (Bisschop et al. 2007; Öberg et al. 2014), and the two molecules are thought to form via different mechanisms (Garrod & Herbst 2006; Garrod et al. 2008). Indeed, in G10.6, we believe the observed correlation likely reflects that both species are tied to total gas column density rather than intrinsic chemical similarity.
5.2. Relationships between Specific Molecules
During our analysis, we noticed three trends that are further explored here: the complex relationship between CH3OCHO and CH3OCH3, tight correlation between HNCO and NH2CHO, and unique temperature dependence of CH3CHO.
5.2.1. CH3OCHO and CH3OCH3
Previous observations of CH3OCHO and CH3OCH3 have revealed nearly constant abundance ratios across a wide range of sources (Jaber et al. 2014; Rivilla et al. 2017; Coletta et al. 2020), remarkably similar spatial distributions (Brouillet et al. 2013), and comparable column densities and gas temperatures (Rong et al. 2016; El-Abd et al. 2019). A chemical link had been previously predicted by modeling (Garrod & Herbst 2006; Garrod et al. 2008) and experimental efforts (Öberg et al. 2009), which indicated a common precursor hypothesis for the formation of CH3OCH3 and CH3OCHO as either involving the CH3O radical (solid phase/ice) or CH3OH (gas phase). Both species can also form through gas-phase chemistry at low temperatures (Balucani et al. 2015), while the presence of additional warm gas-phase pathways cannot be excluded. A summary of the most commonly considered formation routes is provided in Table 4.
Since all proposed formation pathways each involve the presence of CH3OH and its photodissociation products, it is unsurprising that we observe strong correlations between CH3OH and both CH3OCH3 and CH3OCHO, respectively, as shown in the bottom panels of Figure 14. For instance, we identify a nearly constant ratio of CH3OCH3 with respect to CH3OH of 2%, which indicates co-formation or a constant conversion of CH3OH into CH3OCH3 at all temperatures. Constant CH3OCH3/CH3OH ratios have been previously observed in MYSOs (Öberg et al. 2014) and suggest the existence of a single link between CH3OH and CH3OCH3. The simplest explanation for this trend is co-desorption of the two ice constituents, following partial conversion of CH3OH into COMs, including CH3OCH3. If so, this ratio serves as an indicator of overall efficiency of conversion of simple ices into more complex ones. Compared to the typical ratios in MYSOs of 14% from Öberg et al. (2014), G10.6 appears to be relatively inefficient in its CH3OCH3 ice conversion. In contrast to CH3OCH3, the CH3OCHO/CH3OH ratio exhibits a multicomponent trend that is not well described by a constant value and cannot be explained by ice chemistry alone. This suggests the presence of multiple formation pathways, and perhaps a mixture of ice and gas-phase chemistry.
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Standard image High-resolution imageThe top panels of Figure 14 show the column density correlation between CH3OCHO and CH3OCH3. We identify a broad one-to-one correlation across G10.6, and then a second, much steeper correlation in both HC1 and HC2, where CH3OCHO is overproduced compared to CH3OCH3. This one-to-one correlation agrees remarkably well with the power-law relation derived by Jaber et al. (2014) across a wide set of ISM sources over many orders of magnitude in column density and is consistent with observed ratios toward hot cores, intermediate-mass star-forming regions, and hot corinos associated with low-mass protostars (Rivilla et al. 2017, and references therein). As this correlation is quite broad over a wide range of CH3OCHO temperatures (60–275 K) and physical locations across G10.6, it is difficult to discern the relative importance of various reactions, e.g., cold versus warm gas versus ice surface chemistry, which in principle may all contribute at some level to this trend, without performing detailed chemical modeling. Regardless of their specific formation mechanisms, CH3OCHO and CH3OCH3 seem to behave in the same way within the bulk of gas, i.e., outside of the hot cores, in G10.6 as they do in many other ISM sources.
The presence of an additional component in the CH3OCHO/CH3OCH3 correlation indicates that this chemical similarity does not extend in the same way to the hot cores in G10.6. While this component is most distinctly associated with HC1, it may also extend to HC2, as shown in the top left panel of Figure 14. Moreover, it is not clear if this trend is being driven by gas temperature or is specific to hot-core-like environments. We find that the majority, but not the entirety, of points within this steep trend exhibit temperatures >275 K. To explain the presence of this trend, we must disentangle the relative contribution of increased CH3OCHO production versus more efficient CH3OCH3 destruction. Interestingly, we do find a steepening of the CH3OCHO/CH3OH correlation and a modest shallowing of the CH3OCH3/CH3OH correlation toward higher CH3OH column densities. This suggests that there is an additional CH3OCHO formation pathway that kicks in within the hot cores, which would also explain the bimodal correlation between CH3OCH3 and CH3OCHO. Further support for the idea that increased CH3OCH3 destruction is not driving the observed high CH3OCHO/CH3OCH3 ratio is found in the models of Garrod et al. (2008), which predict a peak gas-phase abundance of CH3OCH3 at ∼200 K. Combined with the fact that CH3OCH3 exhibits its highest column densities in the MR, which is exposed to strong radiation fields from the nearby ionized gas in B5, it is unlikely that CH3OCH3 is being readily destroyed from high temperatures within the hot cores.
Observations of anticorrelations between CH3OCHO and formic acid in Orion KL (Neill et al. 2011; Brouillet et al. 2013) have suggested that the production of CH3OCHO is driven by gas-phase reactions (pathway [3] in Table 4) at high gas temperatures. In support of this explanation, ice chemistry pathways are not thought to be efficient at high temperatures, because the models of Garrod et al. (2008) predict a peak CH3OCHO abundance at relatively low temperatures (∼80 K). Thus, one possible explanation for this additional, hot-core-dominated trend in G10.6 is gas-phase reactions driving extra production of CH3OCHO. If CH3OCH3 is forming via ice conversion, which is supported by the constant, temperature-independent CH3OCH3/CH3OH ratio across G10.6, i.e., inside and outside hot cores, then provided that the CH3OCHO gas-phase reaction is sufficiently efficient, this would naturally explain the existence of the observed steeper trend.
5.2.2. HNCO and NH2CHO
Single-dish observations, which found a constant HNCO/NH2CHO abundance ratio in a range of source luminosities and masses (Bisschop et al. 2007; López-Sepulcre et al. 2015), suggested that these molecules were chemically related. Evidence of co-spatial emission in the low-mass protobinary system IRAS 16293 (Coutens et al. 2016), two high-mass cores in G35.20 (Allen et al. 2017), and six cores across three massive star-forming regions (Allen et al. 2020) further indicated a link between the two species.
Figure 15 illustrates the observed HNCO/NH2CHO column density correlation across G10.6. This correlation is strong with a Pearson's correlation coefficient of r = 0.87 and extends more than two orders of magnitude in NH2CHO and three orders of magnitude in HNCO. It is well characterized by a single power law given by [. Neither HC1 nor HC2 exhibits any significant deviations from this trend, which also appears insensitive to temperature, with HNCO rotational temperatures spanning approximately 200 K. In addition, NH2CHO/HNCO ratios within G10.6 closely resemble those previously observed in a sample of low- and intermediate-mass prestellar and protostellar objects (López-Sepulcre et al. 2015). This consistency is further illustrated in the spatially resolved map of NH2CHO/HNCO ratio shown in Figure 16. The majority (60%) of our map is consistent with the ratios derived in López-Sepulcre et al. (2015). The highest NH2CHO/HNCO ratios, which show the largest deviations, are mostly located at peripheries, where NH2CHO line intensities are weaker and uncertainties correspondingly elevated.
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Standard image High-resolution imageDownload figure:
Standard image High-resolution imageThe spatial distributions of both species also provide valuable information about their formation mechanisms. As noted in Section 4.2, column density maps show that HNCO is more spatially extended than NH2CHO. Specifically, NH2CHO is never observed in a region lacking HNCO emission. Not only does NH2CHO possess a spatially limited map of column density, it also displays the most compact map of integrated intensity of all COMs in our sample (Figure 2). Particularly salient is the absence of any detectable NH2CHO toward B3, which otherwise exhibits emission from all other COMs, including HNCO, in our sample. Although difficult to disentangle from the intrinsic excitation characteristics of each species, i.e., Table 2, this nonetheless seems to suggest that the formation of NH2CHO in detectable amounts depends on the presence of hot-core-like physical environments and not simply on the presence of HNCO.
A variety of explanations have been put forth to explain the empirical relationship between HNCO and NH2CHO. Charnley (1997) suggested that NH2CHO forms via the hydrogenation of HNCO, but this route has been challenged by subsequent experimental work (Noble et al. 2015). Simultaneous formation in ices has been explored experimentally (Jones et al. 2011; Fedoseev et al. 2016; Ligterink et al. 2018), and gas-phase pathways (Kahane et al. 2013; Barone et al. 2015; Codella et al. 2017) have also been proposed. Other models (Quénard et al. 2018) argue that the observed HNCO/NH2CHO correlation is instead due to both species responding in similar ways to physical parameters, such as temperature, rather than a direct chemical link between the two species. In light of this finding, the strong correlation observed here warrants a further investigation into the relationship between these molecules in G10.6.
5.2.3. CH3CHO
Based on both single-dish and spatially resolved observations of MYSOs, Öberg et al. (2014) found that CH3CHO displays an overall negative dependence on temperature. Specifically, at low column densities and temperatures (<100 K) the CH3CHO/CH3OH ratio was almost constant at a few per cent, and then dropped dramatically by several orders of magnitude when >100 K. However, several outliers in the form of high CH3CHO/CH3OH ratios even at >100 K hinted at the presence of an additional high-temperature formation pathway for CH3CHO. Notably, all of these outliers were derived from spatially resolved observations, which suggests that these increased CH3CHO abundances may be a common feature of hot-core chemistry.
We observe the presence of two such CH3CHO formation pathways explicitly in G10.6, as shown in Figure 13, where superimposed trend lines are shown to illustrate the presence of these two distinct components. A positive association with temperature is only found in HC1, which indicates the activation of a lukewarm formation pathway at approximately 30 K. Outside of HC1, we see a tight negative correlation with temperature, indicating that the bulk of the CH3CHO gas is forming via this cold route, and perhaps rapidly degrades in lukewarm regions. Thus, single-dish studies, or otherwise low-spatial-resolution observations of MYSOs that cannot resolve hot cores, would likely be dominated by this cold component.
Although less pronounced than in CH3CHO, there is evidence of a similar two-component formation pathway for NH2CHO. The bulk of NH2CHO in G10.6 seems to form efficiently at low temperatures (50–90 K), while in HC1, an extremely tight, positive association with temperature is present. This hot-core component becomes activated around 60 K and continues until nearly 150 K. Thus, there likely exists an efficient low-temperature formation pathway for these molecules, which decreases in efficiency with temperature, but then at very elevated temperatures the species are released from the ice, along with the majority of COMs, resulting in high abundances in HC1.
The formation route of CH3CHO remains unclear, because the relative contributions of gas-phase and grain surface chemistry are not well understood. Grain surface models (Garrod & Herbst 2006; Garrod 2013) and laboratory experiments (e.g., Bennett et al. 2005; Öberg et al. 2009) have predicted that CH3CHO forms via the combination of radicals CH3 and HCO on grain mantles. However, recent quantum chemistry computations by Enrique-Romero et al. (2016, 2019) show that this may be inefficient, as additional pathways resulting in CH4 and CO are competitive. Alternatively, gas-phase models suggest oxidation of hydrocarbons as the primary formation route. Specifically, the release of C2H6 from dust surfaces is expected to drive production of CH3CH2, which in turns reacts in the gas phase with atomic oxygen to form CH3CHO (Charnley 2004). A summary of these proposed ice surface and gas-phase formation pathways is listed in Table 4.
De Simone et al. (2020) showed that a gas-phase route is responsible for CH3CHO production in the outflows of NGC 1333 IRAS 4A. The rotational temperatures (∼10–30 K) in these outflows are comparable to those associated with the low-temperature component in G10.6, which suggests that the bulk of CH3CHO gas may also be forming via gas-phase reactions. A similar finding was reported by Codella et al. (2017), in which gas-phase formation of NH2CHO was confirmed in L1157-B1. Since the temperatures (20–80 K) associated with the B1 cavities (e.g., Gómez-Ruiz et al. 2015) are similar to those in the cold component of NH2CHO, this again may point to gas-phase formation. Although extrapolating conclusions from regions of shock chemistry is not without caveats, these results nonetheless suggest that both cold components for CH3CHO and NH2CHO have their origins in gas-phase reactions in G10.6.
5.3. Comparisons with Other Sources
5.3.1. Massive Star-forming Regions
To quantify how typical HC1 and HC2 in G10.6 are relative to other well-known MYSOs, we compared them against spatially resolved data from: AFGL 4176 (Bøgelund et al. 2019); G34.26 (Mookerjea et al. 2007); G35.20 A, B1–3, and G35.03 A (Allen et al. 2017); IRAS 16562-3959, central compact (CC) core (Guzmán et al. 2018); NGC 7538S, MM1 (Feng et al. 2016); Sgr B2, N2–5 (Bonfand et al. 2017, 2019); and Core 3, W43-MM1 (Molet et al. 2019).
Figure 17 shows the fractional abundances with respect to CH3OH of G10.6 and the literature sample. Both G10.6 cores have relatively high CH3OH column densities (>1018 cm−2), which place them in the top half of the comparison sample. Both cores also exhibit the two lowest CH3OCH3 abundances, while HC1 possesses the lowest CH3CHO abundance and HC2 is fourth lowest. However, besides these two species, both HC1 and HC2 are consistent with literature values and both appear quite typical for massive cores in their relative compositions.
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Standard image High-resolution imageWe next explore COM column density ratios, which often serve as important signposts of evolutionary state and provide constraints on the chemistry occurring within particular sources (e.g., Fontani et al. 2007; Suzuki et al. 2018). Figure 18 compares column density ratios in both hot cores with those in the literature sample of MYSOs. HC1 and HC2 consistently deviate by up to two orders of magnitude from the MYSO sample in ratios among CH3CHO, CH3OCH3, and CH3OCHO. These discrepancies are readily understood by recalling that in Figure 17 HC1 and HC2 are shown to be unusually poor in CH3CHO and CH3OCH3, and present CH3OCHO abundances in the upper range of what has been previously observed. In addition, HC1 may be unusual in its efficient CH3OCHO formation, perhaps due to unique conditions favoring gas-phase formation (see Section 5.2.1).
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Standard image High-resolution imageN-bearing species, such as CH2CHCN/HNCO, NH2CHO/HNCO, and NH2CHO/CH2CHCN, exhibit substantially narrower ranges of ratios than O-bearing COMs. In particular, HC1 and HC2 appear more typical than other MYSOs, and more consistent with each other, i.e., within factors of a few, in their overall N chemistry. The one exception to this trend is that of the complex cyanides, namely the CH3CN/CH3CH2CN and CH3CN/CH2CHCN ratios, which are elevated in both HC1 and HC2.
The ratio of CH2CHCN to CH3CH2CN is sensitive to physical parameters of hot cores (Caselli et al. 1993) and has been used as an estimator of evolutionary age (e.g., Fontani et al. 2007). We find CH2CHCN/CH3CH2CN ratios of 0.49 ± 0.30 and 0.23 ± 0.04 for HC1 and HC2, respectively. These are both consistent with the MYSO comparison sample (0.3–0.9), and the values (0.3–0.5) reported in Fontani et al. (2007) for a single-dish survey of well-known hot cores. Since chemical models predict a sharp decrease in the abundances of CH2CHCN and CH3CH2CN after ∼105 yr (Caselli et al. 1993), the detection of both molecules and their consistent ratios in both cores suggest that they are younger than ≲105 yr with HC2 likely being a factor of a few younger than HC1. More specific conclusions require detailed chemical modeling, especially since Charnley et al. (1992) and Rodgers & Charnley (2001) have suggested that additional gas-phase reactions are important for CH2CHCN production, while Allen et al. (2018) demonstrated that a shorter warm-up phase can also reproduce observed cyanide abundances.
5.3.2. Galactic Center Clouds, Comets, and Low-mass Star-forming Regions
To better understand COM trends across different physical environments, Figure 19 compares COM column densities in HC1 and HC2 with a variety of different ISM sources, including Galactic center (GC) clouds, comets, and low-mass YSOs (LYSOs). COM abundances are remarkably similar across this wide set of sources, which suggests that the underlying chemistry is not greatly sensitive to variations in physical environments. In particular, N-bearing species, e.g., NH2CHO, CH3CN, and CH3CH2CN, exhibit relatively consistent abundances across different types of sources, while O-bearing COMs display larger variations. In particular, CH3OCH3 is underabundant by at least an order of magnitude in both hot cores, while CH3OCHO is enhanced in HC1 by a factor of a few relative to all other sources. These differences are another indicator, similar to the unusual COM ratios seen in Section 5.3.1, of the relative deficits or overabundances in the derived column densities of these species and further establish their relative significance.
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Standard image High-resolution imageCH3CHO exhibits the largest spread across source types. Öberg et al. (2014) found that spatially resolved hot cores exhibited higher CH3CHO/CH3OH ratios than those inferred from single-dish observations. We confirm the existence of this trend by comparing observations of unresolved MYSOs versus those that are spatially resolved. The spatially resolved values are reduced by up to two orders of magnitude in CH3CHO/CH3OH. We do not see a similar trend in the LYSOs, which have nearly the same CH3CHO/CH3OH ratios for both types of observations. Based on Figure 19, the majority of other COMs have consistent abundances between their resolved and unresolved samples, which confirms that CH3CHO/COMs ratios in MYSOs are lower for unresolved observations.
This trend is best understood by first contrasting single-dish observations of LYSOs and MYSOs. In the case of LYSOs, large beam sizes result in observations dominated by cold protostellar envelopes, where, due to their low temperatures, CH3CHO is expected to be abundant. However, this is not the case for MYSOs, which exhibit higher temperatures in their envelopes and surrounding gas structures. But as seen in Öberg et al. (2014) and here in G10.6, there is a rapid fall-off in CH3CHO abundances at higher temperatures. Moreover, unresolved observations of MYSOs are not sensitive to high CH3CHO column densities associated with hot-core chemistry. The combination of these factors leads to dramatically reduced CH3CHO/CH3OH ratios, as is clearly seen in Figure 19. In this scenario, the intermediate CH3CHO/CH3OH ratios of HC1 and HC2, i.e., between those of the unresolved and resolved MYSO samples, are naturally explained by the fact that both hot cores are only marginally resolved in our observations of G10.6.
If this explanation is true, we would expect CH3CHO/CH3OH ratios in cold clouds, which do not possess hot-core chemistry and contain only cold gas, to be comparable to or larger than those from single-dish studies of LYSOs. Recent observations of several starless and prestellar cores in Taurus by Scibelli & Shirley (2020) provide a helpful comparison sample for this purpose. Scibelli & Shirley (2020) found a median CH3CHO/CH3OH ratio of ∼0.09, which is indeed slightly larger than that associated with single-dish studies of LYSOs.
6. Conclusions
We have presented ALMA high-spatial-resolution observations of the COM chemistry in the massive star-forming region G10.6 at 1.3 mm. These observations reveal that while hot-core chemistry appears consistent over many different environments, the chemistry of surrounding COM structures is much more varied and complex. Importantly, the discovery of extended COM structures throughout the central 20,000 au region of G10.6 illustrates that COM chemistry is not only confined to hot molecular cores, but is likely more generally associated with massive star-forming regions. The highly structured nature of these COM features hints at the importance of interactions between hot, ionized gas and nearby surrounding dense gas.
In addition to having important implications for models of such regions (e.g., external heating), our results further reinforce the need for high-spatial-resolution observations and suggest that the small-scale distributions of COMs can provide crucial insight into the physical and chemical processes associated with massive star formation. These results also highlight the need for more observations at intermediate spatial resolutions, which are sensitive to larger physical scales, to properly characterize COM emission. This is best demonstrated by COMs such as CH3CHO, for instance, where insufficient resolution, e.g., single-dish observations, would not capture core-scale lukewarm chemistry, while very high angular resolutions would instead filter out more extended cold-gas chemistry.
We identify a variety of chemical trends, e.g., CH3OCH3/CH3OCHO and HNCO/NH2CHO, previously observed in samples of diverse ISM sources, to also hold true within G10.6 in a spatially resolved manner. Moreover, they often behave in the very same way, i.e., power-law slopes and column density ratios, as they do in these other sources, suggesting that the underlying COM chemistry is tightly linked. Despite this broad agreement, we also observe several unexpected trends, including a spatial distribution of CH3OCH3 that is strikingly dissimilar to that of CH3OCHO and an overabundance of CH3OCHO within at least one hot core. These findings suggest that our current understanding of COM chemistry remains incomplete and provide valuable inputs for chemical models.
This paper makes use of the following ALMA data: ADS/JAO.ALMA #2015.1.00106.S. ALMA is a partnership of ESO (representing its member states), NSF (USA) and NINS (Japan), together with NRC (Canada) and NSC and ASIAA (Taiwan), in cooperation with the Republic of Chile. The Joint ALMA Observatory is operated by ESO, AUI/NRAO, and NAOJ. The National Radio Astronomy Observatory is a facility of the National Science Foundation operated under cooperative agreement by Associated Universities, Inc.
The authors thank the anonymous referees for valuable comments that improved both the content and presentation of this work. This manuscript benefited greatly from the helpful comments of David Wilner and Alyssa Goodman. C.J.L. also thanks Ryan Loomis and Rafael Martín-Doménech for discussions concerning the COM line fitting process. C.J.L. acknowledges funding from the National Science Foundation Graduate Research Fellowship under grant DGE1745303. K.I.Ö. acknowledges funding from the Simons Collaboration on the Origins of Life (SCOL #321183, KÖ). R.G.M. acknowledges support from UNAM-PAPIIT project IN104319. H.B.L. is supported by the Ministry of Science and Technology (MoST) of Taiwan (grant No. 108-2112-M-001-002-MY3). P.T.P.H. is supported by Ministry of Science and Technology (MoST) of Taiwan grant MOST 108-2112-M-001-016-MY2.
Facility: ALMA. -
Software: Astropy (Astropy Collaboration et al. 2013), CASA (McMullin et al. 2007), emcee (Foreman-Mackey et al. 2013), MADCUBA (Martín et al. 2019), Matplotlib (Hunter 2007), NumPy (van der Walt et al. 2011).
Appendix A: Full Spectral Coverage
Figure 20 shows the remaining half of our spectral coverage toward the same representative positions as in Figure 3.
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Standard image High-resolution imageAppendix B: COM Kinematics in G10.6
In Figure 21, we examine the velocities of the same lines as in Figure 2. We find a coherent velocity gradient of ∼10 km s−1 along the NW–SE direction both in individual transitions of single molecules and across the entire sample of species. The velocities of NH2CHO appear to be systematically blueshifted relative to the other COMs, which may indicate that the emission originates from a different spatial region due to chemical layering or an expanding or contracting shell of gas. The velocities of CH3CHO are also modestly blueshifted, and given that both NH2CHO and CH3CHO are among the molecules with the lowest temperatures in G10.6, it is possible that they both arise from a similar region that is distinct from that of the remainder of the warmer COMs.
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Standard image High-resolution imageAppendix C: Details of Line Data Analysis
Below, we present a detailed description of the entire analysis process, from the initial pixel-masking to the derivation of maps of rotational temperature and column density.
C.1. Line Fitting
Integrated intensities for each observed line were determined by fitting a single Gaussian profile to each feature. For lines with substantial wings, only the central peak was used in deriving column densities. Unresolved multiplets originating from the same species were treated as a single line by combining the degeneracies and line intensities.
For each transition, a mask corresponding to a 5
Since G10.6 is line-rich, blending is occasionally present, especially near regions of denser gas with large line widths (e.g., HC1 and, to a lesser extent, HC2). In general, lines that were not unambiguously free from blending throughout G10.6 are not included in the analysis. For each transition of each species, we randomly selected a set of a few hundred fits across G10.6 and confirmed via visual inspection that the fitting process was accurately capturing the observed line properties. During this process, we removed all blended transitions from the analysis. In a few rare cases, line blending was due to a nearby transition originating from the same species, e.g., the K = 0 and K = 1 lines of the J = 12–11 ladder of . In such cases, we treated them as a single line by fitting a single Gaussian and combining line characteristics.
C.2. Derivation of Rotational Temperature and Column Density
For each such pixel, we calculated column density and rotational temperature. Assuming optically thin emission, the column density of molecules in the upper state of each transition is related to the emission surface brightness I
where Aul is the Einstein coefficient and
where S
The upper-state level population Nu is related to the total column density NT by the equation
where gu is the degeneracy of the upper-state level, Q is the partition function, Trot is the rotational temperature, and Eu is the upper-state energy.
The frequencies, line strengths, and upper-state energies of the observed lines of CH3OH are summarized in Table 5, along with the complete set of unblended lines for all molecules included in our sample. In general, line characteristics were taken from the JPL 5 and CDMS 6 catalogs, as indicated in Table 2. We note that catalogs sometime differ in their consideration of nuclear spin in their Einstein A values and partition functions. Care therefore was taken to use matching Einstein A values and partition functions. Partition functions were linearly interpolated from catalog values for all molecules, except for CH3OCHO, where the relative contributions from the vibrational and torsional states are over 40%. In this case, we used the complete rotational–torsional–vibrational partition function from Carvajal et al. (2019).
Table 5. Properties of Unblended Transitions
Transition |
| Eu (K) | gu | Line List | |
---|---|---|---|---|---|
CH3OH | |||||
42,3–31,2, E | 218.4401 | 45.5 | −4.32910 | 9 | CDMS |
42,3–51,4, A | 234.6834 | 60.9 | −4.72715 | 9 | CDMS |
80,8–71,6, E | 220.0786 | 96.6 | −4.59927 | 17 | CDMS |
102,9–93,6, A | 231.2811 | 165.4 | −4.73685 | 21 | CDMS |
102,8–93,7, A | 232.4185 | 165.4 | −4.72826 | 21 | CDMS |
183,16–174,13, A | 232.7834 | 446.5 | −4.66380 | 37 | CDMS |
183,15–174,14, A | 233.7957 | 446.6 | −4.65725 | 37 | CDMS |
201,19–200,20, E | 217.8865 | 508.4 | −4.47125 | 41 | CDMS |
235,19–226,17, E | 219.9937 | 775.9 | −4.75652 | 47 | CDMS |
253,22–244,20, E | 219.9837 | 802.2 | −4.69035 | 51 | CDMS |
13CH3OH | |||||
51,5–41,4, A | 234.0116 | 48.3 | −4.27824 | 11 | CDMS |
102,8–93,7, A | 217.3996 | 162.4 | −4.81610 | 21 | CDMS |
141,13–132,12, A | 217.0446 | 254.3 | −4.62441 | 29 | CDMS |
177,10–186,13, A | 220.3218 | 592.3 | −4.88725 | 35 | CDMS |
177,11–186,12, A | 220.3218 | 592.3 | −4.88725 | 35 | CDMS |
221,21–220,22, E | 231.8184 | 593.9 | −4.41192 | 45 | CDMS |
CH3OCH3 | |||||
130,13–121,12, AA | 231.9879 | 80.9 | −4.03882 | 270 | CDMS |
130,13–121,12, EE | 231.9879 | 80.9 | −4.03884 | 432 | CDMS |
130,13–121,12, AE | 231.9879 | 80.9 | −4.03887 | 162 | CDMS |
130,13–121,12, EA | 231.9879 | 80.9 | −4.03888 | 108 | CDMS |
234,20–233,21, AA | 220.8950 | 274.4 | −4.24596 | 282 | CMDS |
234,20–233,21, EE | 220.8934 | 274.4 | −4.24603 | 752 | CDMS |
234,20–233,21, AE | 220.8918 | 274.4 | −4.24604 | 94 | CDMS |
234,20–233,21, EA | 220.8918 | 274.4 | −4.24597 | 188 | CDMS |
244,20–235,19, AA | 220.8465 | 297.5 | −4.79796 | 294 | CDMS |
244,20–235,19, EE | 220.8476 | 297.5 | −4.79793 | 784 | CDMS |
244,20–235,19, AE | 220.8487 | 297.5 | −4.79804 | 98 | CDMS |
244,20–235,19, EA | 220.8488 | 297.5 | −4.79797 | 196 | CDMS |
255,20–254,21, AA | 233.6329 | 331.9 | −4.13499 | 510 | CDMS |
255,20–254,21, EE | 233.6323 | 331.9 | −4.13491 | 816 | CDMS |
255,20–254,21, AE | 233.6319 | 331.9 | −4.13494 | 306 | CDMS |
255,20–254,21, EA | 233.6316 | 331.9 | −4.13495 | 204 | CDMS |
347,27–338,26, AA | 217.9489 | 611.5 | −4.83593 | 414 | CDMS |
347,27–338,26, AE | 217.9481 | 611.5 | −4.83601 | 138 | CDMS |
347,27–338,26, EA | 217.9483 | 611.5 | −4.84024 | 276 | CDMS |
364,32–363,33, AA | 217.1775 | 638.6 | −4.20439 | 438 | CDMS |
364,32–363,33, AE | 217.1766 | 638.6 | −4.20447 | 146 | CMDS |
364,32–363,33, EA | 217.1766 | 638.6 | −4.20440 | 292 | CDMS |
374,33–373,34, AA | 232.3838 | 673.0 | −4.13634 | 750 | CDMS |
374,33–373,34, EA | 232.3827 | 673.0 | −4.13630 | 300 | CDMS |
374,33–373,34, AE | 232.3827 | 673.0 | −4.13629 | 450 | CDMS |
CH3OCHO | |||||
173,14–163,13, E | 218.2808 | 99.7 | −3.82170 | 70 | JPL |
173,14–163,13, A | 218.2978 | 99.7 | −3.82148 | 70 | JPL |
174,13–164,12, A | 220.1902 | 103.1 | −3.81694 | 70 | JPL |
174,13–164,12, E | 220.1669 | 103.2 | −3.81717 | 70 | JPL |
201,20–191,19, E | 216.9648 | 111.5 | −3.81496 | 82 | JPL |
201,20–191,19, A | 216.9660 | 111.5 | −3.81488 | 82 | JPL |
200,20–190,19, E | 216.9662 | 111.5 | −3.81495 | 82 | JPL |
200,20–190,19, A | 216.9673 | 111.5 | −3.81478 | 82 | JPL |
184,14–174,13, A | 233.7775 | 114.4 | −3.73540 | 74 | JPL |
184,14–174,13, E | 233.7540 | 114.4 | −3.73553 | 74 | JPL |
194,16–184,15, A | 233.2267 | 123.3 | −3.74021 | 78 | JPL |
194,16–184,15, E | 233.2128 | 123.3 | −3.74032 | 78 | JPL |
199,11–189,10, E | 234.5086 | 166.0 | −3.82053 | 78 | JPL |
199,11–189,10, A | 234.5022 | 166.0 | −3.82043 | 78 | JPL |
199,10–189,9, A | 234.5024 | 166.0 | −3.82043 | 78 | JPL |
199,10–189,9, E | 234.4864 | 166.0 | −3.82065 | 78 | JPL |
1910,9–1810,8, E | 234.1123 | 178.5 | −3.85309 | 78 | JPL |
1910,10–1810,9, E | 234.1346 | 178.5 | −3.85297 | 78 | JPL |
1910,10–1810,9, A | 234.1249 | 178.5 | −3.85298 | 78 | JPL |
1910,9–1810,8, A | 234.1249 | 178.5 | −3.85298 | 78 | JPL |
1911,9–1811,8, E | 233.8671 | 192.4 | −3.89076 | 78 | JPL |
1911,8–1811,7, E | 233.8453 | 192.4 | −3.89088 | 78 | JPL |
1911,9–1811,8, A | 233.8542 | 192.4 | −3.89077 | 78 | JPL |
1911,8–1811,7, A | 233.8542 | 192.4 | −3.89077 | 78 | JPL |
1912,8–1812,7, E | 233.6710 | 207.6 | −3.93548 | 78 | JPL |
1912,7–1812,6, A | 233.6553 | 207.6 | −3.93559 | 78 | JPL |
1912,8–1812,7, A | 233.6553 | 207.6 | −3.93559 | 78 | JPL |
1912,7–1812,6, E | 233.6499 | 207.6 | −3.93560 | 78 | JPL |
1913,7–1813,6, E | 233.5246 | 224.2 | −3.98927 | 78 | JPL |
1913,6–1813,5, E | 233.5050 | 224.2 | −3.98949 | 78 | JPL |
1913,6–1813,5, A | 233.5066 | 224.2 | −3.98938 | 78 | JPL |
1913,7–1813,6, A | 233.5066 | 224.2 | −3.98938 | 78 | JPL |
1914,6–1814,5, E | 233.4144 | 242.1 | −4.05557 | 78 | JPL |
1914,5–1814,4, A | 233.3945 | 242.1 | −4.05568 | 78 | JPL |
1914,6–1814,5, A | 233.3945 | 242.1 | −4.05568 | 78 | JPL |
1914,5–1814,4, E | 233.3967 | 242.1 | −4.05578 | 78 | JPL |
1915,5–1815,4, E | 233.3312 | 261.3 | −4.13989 | 78 | JPL |
1915,4–1815,3, E | 233.3158 | 261.3 | −4.14000 | 78 | JPL |
1915,4–1815,3, A | 233.3100 | 261.3 | −4.14001 | 78 | JPL |
1915,5–1815,4, A | 233.3100 | 261.3 | −4.14001 | 78 | JPL |
1816,2–1716,1, A | 220.9262 | 270.7 | −4.46555 | 74 | JPL |
1816,3–1716,2, A | 220.9262 | 270.7 | −4.46555 | 74 | JPL |
1916,4–1816,3, E | 233.2686 | 281.8 | −4.25236 | 78 | JPL |
1916,3–1816,2, A | 233.2466 | 281.9 | −4.25247 | 78 | JPL |
1916,4–1816,3, A | 233.2466 | 281.9 | −4.25247 | 78 | JPL |
CH3CHO | |||||
122,10–112,9, E | 234.7955 | 81.9 | −3.35208 | 50 | JPL |
123,9–113,8, E | 231.8476 | 92.6 | −3.38760 | 50 | JPL |
123,10–113,9, A | 231.5953 | 92.6 | −3.38561 | 50 | JPL |
124,9–114,8, E | 231.5063 | 108.3 | −3.40929 | 50 | JPL |
124,8–114,7, E | 231.4844 | 108.3 | −3.40927 | 50 | JPL |
124,9–114,8, A | 231.4567 | 108.4 | −3.40933 | 50 | JPL |
125,8–115,7, E | 231.3698 | 128.5 | −3.44161 | 50 | JPL |
125,7–115,6, E | 231.3633 | 128.5 | −3.44168 | 50 | JPL |
125,8–115,7, A | 231.3296 | 128.6 | −3.44164 | 50 | JPL |
125,7–115,6, A | 231.3296 | 128.6 | −3.44164 | 50 | JPL |
126,7–116,6, A | 231.2699 | 153.4 | −3.48413 | 50 | JPL |
126,6–116,5, A | 231.2699 | 153.4 | −3.48413 | 50 | JPL |
127,5–117,4, A | 231.2450 | 182.6 | −3.53997 | 50 | JPL |
127,6–117,5, A | 231.2450 | 182.6 | −3.53997 | 50 | JPL |
NH2CHO | |||||
101,9–91,8 | 218.4592 | 60.8 | −3.12640 | 21 | CDMS |
112,10–102,9 | 232.2736 | 78.9 | −3.05471 | 23 | CDMS |
113,9–103,8 | 233.8966 | 94.1 | −3.06449 | 23 | CDMS |
113,8–103,7 | 234.3155 | 94.2 | −3.06216 | 23 | CDMS |
114,8–104,7 | 233.7347 | 114.9 | −3.09334 | 23 | CDMS |
114,7–104,6 | 233.7456 | 114.9 | −3.09332 | 23 | CDMS |
115,6–105,5 | 233.5945 | 141.7 | −3.13303 | 23 | CDMS |
115,7–105,6 | 233.5945 | 141.7 | −3.13303 | 23 | CDMS |
116,5–106,4 | 233.5278 | 174.5 | −3.18626 | 23 | CDMS |
116,6–106,5 | 233.5278 | 174.5 | −3.18626 | 23 | CDMS |
CH3CN | |||||
120–110 | 220.7473 | 68.9 | −3.19582 | 50 | JPL |
121–111 | 220.7430 | 76.0 | −3.19899 | 50 | JPL |
122–112 | 220.7303 | 97.4 | −3.20818 | 50 | JPL |
123–113 | 220.7090 | 133.2 | −3.22415 | 100 | JPL |
124–114 | 220.6793 | 183.2 | −3.24741 | 50 | JPL |
125–115 | 220.6411 | 247.4 | −3.27937 | 50 | JPL |
126–116 | 220.5944 | 325.9 | −3.32175 | 100 | JPL |
127–117 | 220.5393 | 418.6 | −3.37778 | 50 | JPL |
128–118 | 220.4758 | 525.6 | −3.45279 | 50 | JPL |
1210–1110 | 220.3236 | 782.0 | −3.71328 | 50 | JPL |
1211–1111 | 220.2350 | 931.4 | −3.99556 | 50 | JPL |
13CH3CN | |||||
130–120 | 232.2342 | 78.0 | −2.96674 | 54 | JPL |
131–121 | 232.2298 | 85.2 | −2.96929 | 54 | JPL |
132–122 | 232.2167 | 106.7 | −2.97723 | 54 | JPL |
133–123 | 232.1949 | 142.4 | −2.99071 | 108 | JPL |
134–124 | 232.1644 | 192.5 | −3.01034 | 54 | JPL |
135–125 | 232.1251 | 256.9 | −3.03683 | 54 | JPL |
136–126 | 232.0772 | 335.5 | −3.07160 | 108 | JPL |
137–127 | 232.0206 | 428.4 | −3.11660 | 54 | JPL |
138–128 | 231.9554 | 535.5 | −3.17503 | 54 | JPL |
1311–1211 | 231.7081 | 942.1 | −3.51635 | 54 | JPL |
120–110 | 220.6381 | 68.8 | −3.03477 | 50 | JPL |
121–111 | 220.6338 | 76.0 | −3.03783 | 50 | JPL |
122–112 | 220.6211 | 97.4 | −3.04713 | 50 | JPL |
123–113 | 220.6000 | 133.1 | −3.06309 | 100 | JPL |
124–114 | 220.5704 | 183.1 | −3.08635 | 50 | JPL |
125–115 | 220.5323 | 247.4 | −3.11821 | 50 | JPL |
126–116 | 220.4859 | 325.9 | −3.16068 | 100 | JPL |
127–117 | 220.4310 | 418.6 | −3.21671 | 50 | JPL |
CH3CH2CN | |||||
84,5–73,4 | 233.8275 | 33.3 | −4.27063 | 17 | CDMS |
84,4–73,5 | 233.8428 | 33.3 | −4.27050 | 17 | CDMS |
123,10–112,9 | 219.9025 | 43.6 | −4.51661 | 25 | CDMS |
222,21–211,20 | 219.4636 | 112.5 | −4.36804 | 45 | CDMS |
242,22–232,21 | 219.5056 | 135.6 | −3.05185 | 49 | CDMS |
243,21–233,20 | 218.3900 | 139.9 | −3.06221 | 49 | CDMS |
252,24–242,23 | 220.6609 | 143.0 | −3.04508 | 51 | CDMS |
261,25–251,24 | 231.3104 | 153.4 | −2.98243 | 53 | CDMS |
270,27–260,26 | 231.9904 | 157.7 | −2.97677 | 55 | CDMS |
270,27–261,26 | 231.3123 | 157.7 | −4.03702 | 55 | CDMS |
271,27–261,26 | 231.8542 | 157.7 | −2.97758 | 55 | CDMS |
271,27–260,26 | 232.5323 | 157.7 | −4.03004 | 55 | CDMS |
263,24–253,23 | 232.7900 | 161.0 | −2.97762 | 53 | CDMS |
264,23–254,22 | 233.6540 | 169.0 | −2.97716 | 53 | CDMS |
264,22–254,21 | 234.4240 | 169.1 | −2.97285 | 53 | CDMS |
265,22–255,21 | 233.4431 | 178.8 | −2.98431 | 53 | CDMS |
265,21–255,20 | 233.4983 | 178.9 | −2.98400 | 53 | CDMS |
267,19–257,18 | 233.0694 | 205.4 | −3.00266 | 53 | CDMS |
267,20–257,19 | 233.0693 | 205.4 | −3.00266 | 53 | CDMS |
268,18–258,17 | 232.9987 | 222.0 | −3.01361 | 53 | CDMS |
268,19–258,18 | 232.9987 | 222.0 | −3.01361 | 53 | CDMS |
269,17–259,16 | 232.9676 | 240.9 | −3.02597 | 53 | CDMS |
269,18–259,17 | 232.9676 | 240.9 | −3.02597 | 53 | CDMS |
2611,15–2511,14 | 232.9755 | 285.2 | −3.05617 | 53 | CDMS |
2611,16–2511,15 | 232.9755 | 285.2 | −3.05617 | 53 | CDMS |
2612,14–2512,13 | 233.0027 | 310.7 | −3.07436 | 53 | CDMS |
2612,15–2512,14 | 233.0027 | 310.7 | −3.07436 | 53 | CDMS |
2613,13–2513,12 | 233.0411 | 338.3 | −3.09506 | 53 | CDMS |
2613,14–2513,13 | 233.0411 | 338.3 | −3.09506 | 53 | CDMS |
2614,12–2514,11 | 233.0889 | 368.2 | −3.11859 | 53 | CDMS |
2614,13–2514,12 | 233.0889 | 368.2 | −3.11859 | 53 | CDMS |
2615,11–2515,10 | 233.1448 | 400.2 | −3.14537 | 53 | CDMS |
2615,12–2515,11 | 233.1448 | 400.2 | −3.14537 | 53 | CDMS |
2617,9–2517,8 | 233.2779 | 470.6 | −3.21101 | 53 | CDMS |
2617,10–2517,9 | 233.2779 | 470.6 | −3.21101 | 53 | CDMS |
2618,8–2518,7 | 233.3540 | 509.1 | −3.25180 | 53 | CDMS |
2618,9–2518,8 | 233.3540 | 509.1 | −3.25180 | 53 | CDMS |
2619,7–2519,6 | 233.4361 | 549.7 | −3.29960 | 53 | CDMS |
2619,8–2519,7 | 233.4361 | 549.7 | −3.29960 | 53 | CDMS |
495,45–494,46 | 233.2363 | 556.0 | −4.22129 | 99 | CDMS |
503,47–503,48 | 233.2366 | 565.2 | −3.16959 | 1 | CDMS |
2622,4–2522,3 | 233.7144 | 684.1 | −3.51299 | 53 | CDMS |
2622,5–2522,4 | 233.7144 | 684.1 | −3.51299 | 53 | CDMS |
2623,3–2523,2 | 233.8174 | 733.1 | −3.62847 | 53 | CDMS |
2623,4–2523,3 | 233.8174 | 733.1 | −3.62847 | 53 | CDMS |
2625,1–2525,0 | 234.0380 | 837.3 | −4.08692 | 53 | CDMS |
2625,2–2525,1 | 234.0380 | 837.3 | −4.08692 | 53 | CDMS |
CH2CHCN | |||||
241,24–231,23 | 220.5614 | 134.9 | −2.55618 | 47 | CDMS |
233,21–223,20 | 218.5851 | 145.3 | −2.53367 | 41 | CDMS |
233,20–223,19 | 219.4006 | 145.5 | −2.52873 | 41 | CDMS |
242,22–232,21 | 231.9523 | 146.8 | −2.49262 | 47 | CDMS |
234,20–224,19 | 218.5736 | 160.4 | −2.53953 | 41 | CDMS |
234,19–224,18 | 218.6151 | 160.4 | −2.53934 | 41 | CDMS |
235,18–225,17 | 218.4524 | 179.8 | −2.54797 | 41 | CDMS |
235,19–225,18 | 218.4513 | 179.8 | −2.54797 | 41 | CDMS |
236,17–226,16 | 218.4025 | 203.5 | −2.55783 | 41 | CDMS |
236,18–226,17 | 218.4024 | 203.5 | −2.55783 | 41 | CDMS |
237,16–227,15 | 218.3986 | 231.5 | −2.56948 | 41 | CDMS |
237,17–227,16 | 218.3986 | 231.5 | −2.56948 | 41 | CDMS |
238,15–228,14 | 218.4218 | 263.8 | −2.58311 | 41 | CDMS |
238,16–228,15 | 218.4218 | 263.8 | −2.58311 | 41 | CDMS |
2310,13–2210,12 | 218.5200 | 341.1 | −2.61750 | 41 | CDMS |
2310,14–2210,13 | 218.5200 | 341.1 | −2.61750 | 41 | CDMS |
2312,11–2212,10 | 218.6665 | 435.0 | −2.66366 | 41 | CDMS |
2312,12–2212,11 | 218.6665 | 435.0 | −2.66366 | 41 | CDMS |
HNCO | |||||
100,10–90,9 | 219.7983 | 58.0 | −3.83290 | 21 | CDMS |
101,9–91,8 | 220.5848 | 101.5 | −3.83753 | 21 | CDMS |
102,8–92,7 | 219.7372 | 228.3 | −3.87103 | 21 | CDMS |
102,9–92,8 | 219.7339 | 228.3 | −3.87104 | 21 | CDMS |
103,7–93,6 | 219.6568 | 433.0 | −3.92039 | 21 | CDMS |
103,8–93,7 | 219.6568 | 433.0 | −3.92039 | 21 | CDMS |
281,28–290,29 | 231.8733 | 469.9 | −4.17514 | 57 | CDMS |
105,5–95,4 | 219.3924 | 1049.5 | −4.09372 | 21 | CDMS |
105,6–95,5 | 219.3924 | 1049.5 | −4.09372 | 21 | CDMS |
As is standard in rotational diagram analysis (e.g., Goldsmith & Langer 1999), taking the logarithm of Equation (C3) gives the linear equation
A semi-log plot of Nu/gu versus upper-state energies Eu allows for the derivation of rotational temperature and total column density from the best-fit slope and intercept, respectively. The optical depth of the observed transitions is unknown a priori, and in regions of high density such as G10.6, we may expect optically thick lines. In this case, i.e., , the optical depth correction factor C
which makes the true level populations
With these corrections, Equation (C4) can be rewritten as
The optical depths of individual transitions can then be related back to the upper-state level populations via
Hence, C
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Standard image High-resolution imageC.3. Line Blending and Example LTE Spectra
To assess the level of blending present, particularly toward dense regions such as HC1, we compared observed spectra with synthetic LTE model spectra generated using the MADCUBA 7 (Madrid Data Cube Analysis) package (Martín et al. 2019). We used the SLIM (Spectral Line Identification and LTE Modelling) tool within MADCUBA, which uses spectroscopic data from the CDMS and JPL catalogs to produce model spectra under LTE conditions for a given set of input physical parameters. For each species in our sample, we inputted the rotational temperature, column density, typical FWHM, and systemic velocity, as derived in Section 3. We fixed the source size to the beam size for all molecules and extracted spectra toward HC1 and MR from a region equal in area to the beam size. Figure 23 shows the LTE model spectrum toward HC1, which has the densest gas and largest line widths in G10.6, and thus we expect maximal line blending to occur toward this region. In general, a moderate degree of line blending is present for some species (e.g., CH3OCHO), but in all cases there are a sufficient number of unblended lines to allow for reliable fits and robust rotational diagrams. Next, in Figure 24, we show an LTE spectrum toward the MR, which is more representative of the gas outside of HC1 and HC2 in G10.6. Here, blending is minimal, due in part to the narrower line widths.
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Standard image High-resolution imageAppendix D: Deriving the 12C/13C Ratio in G10.6
Due to the sparse number of observed 13CH3OH transitions, we adopted the well-constrained rotational temperature from the main species CH3OH. Toward HC1, we only detected two high-Eu transitions (592 and 594 K) and one low-Eu (162 K) line. The high uncertainties associated with the integrated intensities of these lines made fitting difficult, resulting in an anomalously high column density. Thus, we purposely excluded HC1 when deriving 13CH3OH column densities. Toward HC2, we only detected the Eu (162 K) line, which also prohibits a determination of column density. The 13CH3OH column density map is shown in the left panel of Figure 25.
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Standard image High-resolution imageIn order to assess the typical 12C/13C ratio in G10.6, we compared the distribution of relative column densities of CH3OH and 13CH3OH in the middle and right panels of Figure 25. The majority of values are clustered about the median column density ratio of 22.8, which is nearly a factor of two lower than the expected ratio of approximately 43 (Milam et al. 2005) at the distance of G10.6 (DGC = 3.9 kpc). Ratios of >40 only occur toward the periphery of the dense gas in G10.6, where line intensities have decreased and are therefore considerably more uncertain and should be interpreted with caution. In the regions used to derive the 12C/13C ratio,
Appendix E: Full Line Lists
The full list of COM transitions used to derive rotational temperatures and column densities is shown in Table 5.
Footnotes
- 4
The observed differences in optical depth between 13CH3CN 13–12 and 12–11 are somewhat surprising, given their similar Aul and Eu values, and may be due to self-absorption, which is not resolved in frequency, line blending, or different 12C/13C ratios for non-equivalent carbon atoms.
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MADCUBA is software developed at the Center of Astrobiology of Madrid (CSIC-INTA) to visualize and analyze astronomical data cubes and spectra. MADCUBA is available at: http://cab.inta-csic.es/madcuba/Portada.html.