Abstract:We quantified the effects of stellar feedback in RCW 49 by determining the physical conditions in different regions using the [C ii] 158 μm and [O i] 63 μm observations from SOFIA, the 12CO (3–2) observations from APEX, and the H2 line observations from Spitzer telescopes. Large maps of RCW 49 were observed with the SOFIA and APEX telescopes, while the Spitzer observations were only available toward three small areas. From our qualitative analysis, we found that the H2 0–0 S(2) emission line probes denser ga… Show more
“…The "northern and southern clouds" reported in Figure 7 of Tiwari et al (2021) are identified as the red-colored cluster. The "pillar," which is reported as an independent structure in Tiwari et al (2022), is identified as a part of the southern cloud here (Figure 5). In previous studies (Tiwari et al 2021(Tiwari et al , 2022, the pillar is reported to be most intense in the velocity range of 5-15 km s −1 , which overlaps with the southern cloud (most intense within the velocity range of 2-8 km s −1 ).…”
Section: Gmm Resultsmentioning
confidence: 77%
“…The "pillar," which is reported as an independent structure in Tiwari et al (2022), is identified as a part of the southern cloud here (Figure 5). In previous studies (Tiwari et al 2021(Tiwari et al , 2022, the pillar is reported to be most intense in the velocity range of 5-15 km s −1 , which overlaps with the southern cloud (most intense within the velocity range of 2-8 km s −1 ). Morphologically, this pillar can be recognized as a separate structure, but kinematically, it is part of the southern cloud.…”
Section: Gmm Resultsmentioning
confidence: 77%
“…Similar to RCW 120, we excluded five that corresponded to noise and were mainly localized on the edges of the map. Observational studies (Furukawa et al 2009;Tiwari et al 2021Tiwari et al , 2022 identified four different physical structures in RCW 49. We identify three of these.…”
Section: Gmm Resultsmentioning
confidence: 99%
“…The stellar winds of the Wd2 cluster and WR20a have swept up a shell of radius 6 pc which expands at a speed of ∼13 km s −1 and has a mass of 2.5 × 10 4 M e . Besides the shell, this region also hosts two large-scale molecular clouds whose collision led to the formation of the Wd2 cluster (Furukawa et al 2009), namely the ridge and the northern and southern clouds (Tiwari et al 2021(Tiwari et al , 2022.…”
Section: Rcw 49mentioning
confidence: 99%
“…These structures can be spatially and spectrally distinct. Their physical conditions are among others dependent on morphology, relative location to the main ionizing source and the star formation history of the region (Tiwari et al 2022). Estimations of these physical conditions quantify the role of stellar feedback in the evolution of the ISM.…”
We explore the potential of the Gaussian mixture model (GMM), an unsupervised machine-learning method, to identify coherent physical structures in the interstellar medium. The implementation we present can be used on any kind of spatially and spectrally resolved data set. We provide a step-by-step guide to use these models on different sources and data sets. Following the guide, we run the models on NGC 1977, RCW 120, and RCW 49 using the [C ii] 158 μm mapping observations from the SOFIA telescope. We find that the models identified six, four, and five velocity coherent physical structures in NGC 1977, RCW 120, and RCW 49, respectively, which are validated by analyzing the observed spectra toward these structures and by comparison to earlier findings. In this work we demonstrate that GMM is a powerful tool that can better automate the process of spatial and spectral analysis to interpret mapping observations.
“…The "northern and southern clouds" reported in Figure 7 of Tiwari et al (2021) are identified as the red-colored cluster. The "pillar," which is reported as an independent structure in Tiwari et al (2022), is identified as a part of the southern cloud here (Figure 5). In previous studies (Tiwari et al 2021(Tiwari et al , 2022, the pillar is reported to be most intense in the velocity range of 5-15 km s −1 , which overlaps with the southern cloud (most intense within the velocity range of 2-8 km s −1 ).…”
Section: Gmm Resultsmentioning
confidence: 77%
“…The "pillar," which is reported as an independent structure in Tiwari et al (2022), is identified as a part of the southern cloud here (Figure 5). In previous studies (Tiwari et al 2021(Tiwari et al , 2022, the pillar is reported to be most intense in the velocity range of 5-15 km s −1 , which overlaps with the southern cloud (most intense within the velocity range of 2-8 km s −1 ). Morphologically, this pillar can be recognized as a separate structure, but kinematically, it is part of the southern cloud.…”
Section: Gmm Resultsmentioning
confidence: 77%
“…Similar to RCW 120, we excluded five that corresponded to noise and were mainly localized on the edges of the map. Observational studies (Furukawa et al 2009;Tiwari et al 2021Tiwari et al , 2022 identified four different physical structures in RCW 49. We identify three of these.…”
Section: Gmm Resultsmentioning
confidence: 99%
“…The stellar winds of the Wd2 cluster and WR20a have swept up a shell of radius 6 pc which expands at a speed of ∼13 km s −1 and has a mass of 2.5 × 10 4 M e . Besides the shell, this region also hosts two large-scale molecular clouds whose collision led to the formation of the Wd2 cluster (Furukawa et al 2009), namely the ridge and the northern and southern clouds (Tiwari et al 2021(Tiwari et al , 2022.…”
Section: Rcw 49mentioning
confidence: 99%
“…These structures can be spatially and spectrally distinct. Their physical conditions are among others dependent on morphology, relative location to the main ionizing source and the star formation history of the region (Tiwari et al 2022). Estimations of these physical conditions quantify the role of stellar feedback in the evolution of the ISM.…”
We explore the potential of the Gaussian mixture model (GMM), an unsupervised machine-learning method, to identify coherent physical structures in the interstellar medium. The implementation we present can be used on any kind of spatially and spectrally resolved data set. We provide a step-by-step guide to use these models on different sources and data sets. Following the guide, we run the models on NGC 1977, RCW 120, and RCW 49 using the [C ii] 158 μm mapping observations from the SOFIA telescope. We find that the models identified six, four, and five velocity coherent physical structures in NGC 1977, RCW 120, and RCW 49, respectively, which are validated by analyzing the observed spectra toward these structures and by comparison to earlier findings. In this work we demonstrate that GMM is a powerful tool that can better automate the process of spatial and spectral analysis to interpret mapping observations.
The PhotoDissociation Region Toolbox provides comprehensive, easy-to-use, public software tools and models that enable an understanding of the interaction of the light of young, luminous, massive stars with the gas and dust in the Milky Way and in other galaxies. It consists of an open-source Python toolkit and photodissociation region (PDR) models for analysis of infrared and millimeter/submillimeter line and continuum observations obtained by ground-based and suborbital telescopes, and astrophysics space missions. PDRs include all of the neutral gas in the interstellar medium where far-ultraviolet photons dominate the chemistry and/or heating. In regions of massive star formation, PDRs are created at the boundaries between the H ii regions and neutral molecular cloud, as photons with energies 6 eV < h
ν < 13.6 eV photodissociate molecules and photoionize metals. The gas is heated by photoelectrons from small grains and large molecules and cools mostly through far-infrared (FIR) fine-structure lines like [O i] and [C ii]. The models are created from state-of-the art PDR codes that include molecular freeze-out; recent collision, chemical, and photorates; new chemical pathways, such as oxygen chemistry; and allow for both clumpy and uniform media. The models predict the emergent intensities of many spectral lines and FIR continuum. The tools find the best-fit models to the observations and provide insight into the physical conditions and chemical makeup of the gas and dust. The PDR Toolbox enables novel analysis of data from telescopes such as the Infrared Space Observatory, Spitzer, Herschel, the Stratospheric Terahertz Observatory, the Stratospheric Observatory for Infrared Astronomy, the Submillimeter Wave Astronomy Satellite, the Atacama Pathfinder Experiment, the Atacama Large Millimeter/submillimeter Array, and the JWST.
We investigate the physical structure and conditions of photodissociation regions (PDRs) and molecular gas within the Pillars of Creation in the Eagle Nebula using SOFIA FEEDBACK observations of the [C ii] 158 μm line. These observations are velocity resolved to 0.5 km s−1 and are analyzed alongside a collection of complimentary data with similar spatial and spectral resolution: the [O i] 63 μm line, also observed with SOFIA, and rotational lines of CO, HCN, HCO+, CS, and N2H+. Using the superb spectral resolution of SOFIA, APEX, CARMA, and BIMA, we reveal the relationships between the warm PDR and cool molecular gas layers in context of the Pillars’ kinematic structure. We assemble a geometric picture of the Pillars and their surroundings informed by illumination patterns and kinematic relationships and derive physical conditions in the PDRs associated with the Pillars. We estimate an average molecular gas density
n
H
2
∼
1.3
×
10
5
cm−3 and an average atomic gas density n
H ∼ 1.8 × 104 cm−3 and infer that the ionized, atomic, and molecular phases are in pressure equilibrium if the atomic gas is magnetically supported. We find pillar masses of 103, 78, 103, and 18 M
⊙ for P1a, P1b, P2, and P3, respectively, and evaporation times of ∼1–2 Myr. The dense clumps at the tops of the pillars are currently supported by the magnetic field. Our analysis suggests that ambipolar diffusion is rapid and these clumps are likely to collapse within their photoevaporation timescales.
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