arXiv subjects

Yoshito Shimajiri

Publications and source records attributed to Yoshito Shimajiri.

At least 19 recordsLinked to original sources

arXiv2026

From inter-filamentary gas to filaments and hubs: gas flows in the Mon R2 hub-filament system

Hub-filament systems (HFSs) play an important role in the formation of massive stars and star clusters. Although the velocity structures along dense filaments have been studied, the gas kinematics in the low density inter-filament regions has not been investigated. We use $^{13}$CO ($J$ = 1--0) and C$^{18}$O ($J$ = 1--0) observations obtained with the Nobeyama 45 m telescope to study the gas dynamics towards the Monoceros R2 (Mon R2) HFS. From the $^{13}$CO and C$^{18}$O data, tracing low- and high-density gas, respectively, we identify velocity coherent structures and divide them into filaments (Fs) and inter-filamentary regions (IFs). We estimate velocity gradients ($Δv$) and mass accretion rates ($\dot{M}$) along ($\parallel$) and across ($\perp$) the Fs and IFs. The mean ratio of $\dot{M}_\parallel$ to $\dot{M}_\perp$ in Fs is 6.8, while that in IFs is 1.5. These results show that the overall gas within both Fs and IFs flows directly into the hub and the gas flows faster along the Fs than the IFs. In addition, we found that at least 30\% of the gas mass in the IFs may flow towards the Fs replenishing the latter with new matter. Our study reveals the importance of considering the total gas mass reservoir, both low- and high-density, infalling into the hub and promoting the formation of massive stars, which are preferentially located in the hub of Mon R2.

astro-ph.GA↗

arXiv2026

Predicting dust temperature from molecular line data using machine learning

We conducted experiments with machine learning techniques to construct dust temperature maps from the CO isotopologue molecular line data in the Orion A molecular cloud. In the classical astrophysical methodology, multi-band continuum data are required to derive the dust temperature. The present study aims to investigate the capability and limitations of machine learning techniques to derive dust temperatures in regions without multi-band dust continuum data. We investigated how the number of pixels used for training influences prediction accuracy, and how the dust temperatures sampled in the training area influence prediction accuracy. We found that $\sim$5\% of the total number of pixels in the observational region is sufficient for training to obtain accurate predictions. Furthermore, a dust temperature sample within the training area should cover the whole temperature range and have a similar sample distribution to that of the entire observing region for an accurate prediction. The $^{12}$CO / $^{13}$CO ratio is often found to be the most important feature in predicting the dust temperature. As the $^{12}$CO / $^{13}$CO ratio is a tracer of PDR, the machine learning technique could connect the dust temperatures to the PDRs. We also found that the condition of thermal gas-dust coupling is not required for accurate prediction of the dust temperature from the molecular line data, and that machine learning is capable of capturing information more than classical astrophysical concepts.

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arXiv2025

Fragmenting Filaments and Evolving Cores -- Insights from Dust Polarisation Study of a filament in Northern Orion B

We present an analysis of polarised dust emission at 850 micron for a parsec long filament in the northern part of the Orion B molecular cloud. The region was observed by the JCMT SCUBA-2/POL-2 polarimeter. The filament has a line mass (~80 Msun/pc) larger than the critical (magnetic) line mass (~37 Msun/pc); and hosts one starless, three prestellar, and four protostellar cores, with masses in the range 0.13 to 9.13 Msun. The mean (debiased) polarisation fraction of the filament and core pixels was calculated to be 5.3+/-0.3% and 3.2+/-0.3%, respectively, likely reflecting their distinct physical conditions. The polarisation fraction for the cores does not depend on the type of core, and was found to decrease with increasing column density, varying from 6-11% at the filament edges to 1$^{+0.7}_{-0.1}$% in the denser parts ($N_{H2}\gtrsim$2x10$^{22}$cm$^{-2}$). Magnetic field orientation of the protostellar cores, in contrast to prestellar cores, appears to be relatively aligned with the magnetic field orientation of the local filament in this region. Using the Davis-Chandrasekhar-Fermi formalism the plane-of-sky magnetic field strength for the protostellar cores (~39-110 microG) was found to be higher than that of the prestellar cores (~22-61 microG); and weakest for the starless core (~6 microG). The average value for the filament was found to be ~31 microG. The magnetic field-volume density relation for the prestellar/starless cores and protostellar cores suggests a transition from weak field case to strong field case as the cores evolve from prestellar to protostellar phase.

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arXiv2025

The LMT 2 millimeter receiver system (B4R). II. Science demonstration observations toward Orion-KL/OMC-1

We present the results of mapping and single-point spectral scans toward Orion-KL/OMC-1 performed as science demonstrations of a 2 mm SIS receiver, the Band 4 Receiver (B4R), installed on the 50 m Large Millimeter Telescope (LMT). To prove the capabilities of mapping and spectral scans with the B4R on the LMT, commissioning observations were conducted employing the on-the-fly mapping technique toward Orion-KL/OMC-1, which covers a map size of 5$'\times$5$'$. These mapping observations were performed with two frequency settings providing 10 GHz in total (131.4-133.9 GHz and 145.1-147.6 GHz; 136.2-138.7 GHz and 149.9-152.4 GHz) with a frequency resolution of 76.293 kHz. We conducted spectral line identification analysis for the hot core and compact ridge regions in the Orion-KL with a beam size of 11-12$''$. We detected nearly 400 emission lines and identified two recombination lines and 29 molecular species, including isotopologues, deuterated molecules, and vibrational excited states, despite the short integration time. These results are consistent with those of previous studies. The 29 molecular species include nitrogen (N)-bearing complex organic molecules (COMs) and oxygen (O)-bearing COMs. To demonstrate the capability of the B4R in astrochemistry, we conducted detailed analyses of column densities, rotational temperatures, and relative abundances with respect to H$_2$ on two representative COMs, N-bearing C$_2$H$_5$CN and O-bearing CH$_3$OCHO in the central 40$''\times$40$''$ area of the map. The wide bandwidth of 10 GHz enabled the use of 8 and 34 emission lines, respectively. The spatial differences in the physical and chemical properties between these molecules were derived at a spatial resolution of $\sim$12$''$. The B4R on the LMT was successfully demonstrated to be powerful for mapping and spectral scans and to have high potential for the study of interstellar chemistry.

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arXiv2025

The LMT 2 Millimeter Receiver System (B4R). I. Overview and Results of Science Demonstration

We report on the results of the on-sky test and science demonstration conducted with the 2 mm receiver system, B4R, on the 50 m Large Millimeter Telescope (LMT), located at an altitude of 4600 m in Mexico. The B4R receiver was developed based on the dual-polarization sideband-separating mixer technology of the Atacama Large Millimeter/submillimeter Array, and is equipped with a fast Fourier transform digital spectrometer, XFFTS. The primary science objective is the spectroscopic redshift identification of high-redshift dusty star-forming galaxies, complementing the existing 3 mm Redshift Search Receiver by enabling the detection of multiple carbon monoxide lines. Additionally, the B4R receiver broadens the range of science cases possible with the LMT, including astrochemistry, as the 2 mm band encompasses unique molecular lines such as deuterated molecules and shock tracers. During on-site commissioning in 2018 and 2019, we successfully demonstrated on-the-fly mapping and position-switching observations toward the Orion Molecular Cloud 1 and bright high-redshift dusty star-forming galaxies, respectively. We confirmed that the installed B4R system largely met its basic performance specifications. Furthermore, we measured the LMT's aperture efficiencies across the entire B4R frequency range (130-160 GHz), finding them to be roughly consistent with expectations based on a surface accuracy of 100 $μ$m and the receiver optics design. These results with the B4R will enable the most sensitive single-dish spectroscopic observations at 2 mm using the LMT.

astro-ph.IM↗

arXiv2025

Infrared bubble recognition in the Milky Way and beyond using deep learning

We propose a deep learning model that can detect Spitzer bubbles accurately using two-wavelength near-infrared data acquired by the Spitzer Space Telescope and JWST. The model is based on the Single Shot MultiBox Detector as an object detection model, trained and validated using Spitzer bubbles identified by the Milky Way Project (MWP-Bubble). We found that using only MWP-Bubbles with clear structures, along with normalization and data augmentation, significantly improved performance. To reduce the dataset bias, we also use the data without bubbles in the dataset selected by combining two techniques: negative sampling and clustering. The model was optimized by hyperparameter tuning using Bayesian optimization. Applying this model to a test region of the Galactic plane resulted in a 98 $\%$ detection rate for MWP-Bubbles with 8 $μ$ m emission clearly encompassing 24 $μ$ m emission. Additionally, we applied the model to a broader area of $1^\circ \leq |l| \leq 65^\circ$, $|b| \leq 1^\circ$, including both training and validation regions, and the model detected 3,006 bubbles, of which 1,413 were newly detected. We also attempted to detect bubbles in the high-mass star-forming region Cygnus $X$, as well as in the external galaxies Large Magellanic Cloud (LMC) and NGC 628. The model successfully detected Spitzer bubbles in these external galaxies, though it also detected Mira-type variable stars and other compact sources that can be difficult to distinguish from Spitzer bubbles. The detection process takes only a few hours, demonstrating the efficiency in detecting bubble structures. Furthermore, the method used for detecting Spitzer bubbles was applied to detect shell-like structures observable only in the 8 $μ$ m emission band, leading to the detection of 469 shell-like structures in the LMC and 143 in NGC 628.

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arXiv2025

Structure and Fragmentation Scale of a Massive Star-Forming Filament in NGC6334: High-Resolution Mid-Infrared Absorption Imaging with JWST

Dense filaments are believed to be representative of the initial conditions of star formation in molecular clouds. We have used the MIRI instrument on JWST to image the massive filament NGC6334M at d~1.3 kpc with unprecedented resolution and dynamic range at 7.7 and 25.5 microns. Our observations reveal the fine structure of the filament in absorption against mid-infrared background emission. From the absorption data, we derive high-resolution column density maps and perform a detailed analysis of the filament structure. We find a median filament width of 0.12+/-0.02 pc at both wavelengths, resolved by almost two orders of magnitude by MIRI, and consistent with the typical half-power width of Herschel filaments in nearby (d<0.5 kpc) clouds. The JWST data also reveal the presence of a quasi-periodic series of side filaments with a similar projected spacing of 0.125+/-0.015 pc. Combining our JWST results with Spitzer and APEX/Herschel data, we perform a study of cloud structure over four orders of magnitude in linear scale. A convergence test shows that our width estimates for NGC6334M are robust and reflect the presence of a true characteristic scale. While there is evidence of a Kolmogorov-like spectrum of small-scale fluctuations down the 1.6x10^-3 pc resolution of the JWST observations, we identify a break in the power spectrum of column density fluctuations at a scale ~0.1-0.4 pc comparable to the width of NGC6334M and its side filaments. This characteristic scale ~0.1pc has important implications for the origin of the star formation efficiency in dense gas and the IMF.

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arXiv2025

Large molecular and dust reservoir of a gravitationally-lensed submillimeter galaxy behind the Lupus-I molecular cloud

We report the Australian Telescope Compact Array and Nobeyama 45 m telescope detection of a remarkably bright $S_\mathrm{1.1mm}$ = 44 mJy) submillimeter galaxy MM J154506.4-344318 in emission lines at 48.5 and 97.0 GHz, respectively. We also identify part of an emission line at $\approx$ 218.3 GHz using the Atacama Large Millimeter/submillimeter Array (ALMA). Together with photometric redshift estimates and the ratio between the line and infrared luminosities, we conclude that the emission lines are most likely to be the $J$ = 2-1, 4-3, and 9-8 transitions of $^{12}$CO at redshift $z = 3.753 \pm 0.001$. ALMA 1.3 mm continuum imaging reveals an arc and a spot separated by an angular distance of 1.6 arcsec, indicative of a strongly-lensed dusty star-forming galaxy with respective molecular and dust masses of $\log{M_{\rm mol}/M_\odot} \approx 11.5$ and $\log{M_{\rm dust}/M_\odot} \approx 9.4$ after corrected for $\approx$ 6.6$\times$ gravitational magnification. The inferred dust-to-gas mass ratio is found to be high ($\approx$ 0.0083) among coeval dusty star-forming galaxies, implying the presence of a massive, chemically-enriched reservoir of cool interstellar medium at $z \approx 4$ or 1.6 Gyr after the Big Bang.

astro-ph.GA↗

arXiv2024

KAgoshima Galactic Object survey with Nobeyama 45-metre telescope by Mapping in Ammonia lines (KAGONMA): Discovery of parsec-scale CO depletion in the Canis Major star-forming region

In observational studies of infrared dark clouds, the number of detections of CO freeze-out onto dust grains (CO depletion) at pc-scale is extremely limited, and the conditions for its occurrence are, therefore, still unknown. We report a new object where pc-scale CO depletion is expected. As a part of Kagoshima Galactic Object survey with Nobeyama 45-m telescope by Mapping in Ammonia lines (KAGONMA), we have made mapping observations of NH3 inversion transition lines towards the star-forming region associated with the CMa OB1 including IRAS 07077-1026, IRAS 07081-1028, and PGCC G224.28-0.82. By comparing the spatial distributions of the NH3 (1,1) and C18O (J=1-0), an intensity anti-correlation was found in IRAS 07077-1026 and IRAS 07081-1028 on the ~1 pc scale. Furthermore, we obtained a lower abundance of C18O at least in IRAS 07077-1026 than in the other parts of the star-forming region. After examining high density gas dissipation, photodissociation, and CO depletion, we concluded that the intensity anti-correlation in IRAS 07077-1026 is due to CO depletion. On the other hand, in the vicinity of the centre of PGCC G224.28-0.82, the emission line intensities of both the NH3 (1,1) and C18O (J=1-0) were strongly detected, although the gas temperature and density were similar to IRAS 07077-1026. This indicates that there are situations where C18O (J=1-0) cannot trace dense gas on the pc scale and implies that the conditional differences that C18O (J=1-0) can and cannot trace dense gas are unclear.

astro-ph.GA↗

arXiv2023

Predicting reliable H$_2$ column density maps from molecular line data using machine learning

The total mass estimate of molecular clouds suffers from the uncertainty in the H$_2$-CO conversion factor, the so-called $X_{\rm CO}$ factor, which is used to convert the $^{12}$CO (1--0) integrated intensity to the H$_2$ column density. We demonstrate the machine learning's ability to predict the H$_2$ column density from the $^{12}$CO, $^{13}$CO, and C$^{18}$O (1--0) data set of four star-forming molecular clouds; Orion A, Orion B, Aquila, and M17. When the training is performed on a subset of each cloud, the overall distribution of the predicted column density is consistent with that of the Herschel column density. The total column density predicted and observed is consistent within 10\%, suggesting that the machine learning prediction provides a reasonable total mass estimate of each cloud. However, the distribution of the column density for values $> \sim 2 \times 10^{22}$ cm$^{-2}$, which corresponds to the dense gas, could not be predicted well. This indicates that molecular line observations tracing the dense gas are required for the training. We also found a significant difference between the predicted and observed column density when we created the model after training the data on different clouds. This highlights the presence of different $X_{\rm CO}$ factors between the clouds, and further training in various clouds is required to correct for these variations. We also demonstrated that this method could predict the column density toward the area not observed by Herschel if the molecular line and column density maps are available for the small portion, and the molecular line data are available for the larger areas.

astro-ph.GA↗

arXiv2023

Dense gas and star formation in the Outer Milky Way

We present maps and spectra of the HCN(1-0) and HCO$^+$(1-0) lines in the extreme outer Galaxy, at galactocentric radii between 14 and 22 kpc, with the 13.7 meter Delingha telescope. The 9 molecular clouds were selected from a CO/$^{13}$CO survey of the outer quadrants. The goal is to better understand the structure of molecular clouds in these poorly studied subsolar metallicity regions and the relation with star formation. The lines are all narrow, less than 2km/s at half power, enabling detection of the HCN hyperfine structure in the stronger sources and allowing us to observationally test hyperfine collision rates. The hyperfine line ratios show that the HCN emission is optically thin with column densities estimated at N(HCN)~$3x10^{12}$\scm. The HCO$^+$ emission is approximately twice as strong as the HCN (taken as the sum of all components), in contrast with the inner Galaxy and nearby galaxies where they are similarly strong. For an abundance ratio $χ_{HCN}/χ_{HCO^+} = 3$, this requires a relatively low density solution for the dense gas, with n(H2) $\sim 10^3 - 10^4$\ccm. The $^{12}$CO/$^{13}$CO line ratios are similar to solar neighborhood values, roughly 7.5, despite the low $^{13}$CO abundance expected at such large radii. The HCO$^+$/CO and HCO$^+$/$^{13}$CO integrated intensity ratios are also standard at about 1/35 and 1/5 respectively. HCN is weak compared to the CO emission, with HCN/CO $\sim 1/70$ even after summing all hyperfine components. At the parsec scales observed here, the correlation between star formation, as traced by 24~$μ$m emission as is standard in extragalactic work, and dense gas via the HCN or HCO$^+$ emission, is poor, perhaps due to the lack of dynamic range. We find that the lowest dense gas fractions are in the sources at high galactic latitude (b>2, h>300pc above the plane), possibly due to lower pressure.

astro-ph.GA↗

arXiv2023

Multi log-normal density structure in Cygnus-X molecular clouds: A fitting for N-PDF without power-law

We studied the H$_2$ column density probability distribution function (N-PDF) based on molecular emission lines using the Nobeyama 45-m Cygnus X CO survey data. Using the DENDROGRAM and SCIMES algorithms, we identified 124 molecular clouds in the $^{13}$CO data. From these identified molecular clouds, an N-PDF was constructed for 11 molecular clouds with an extent of more than 0.4 deg$^2$. From the fitting of the N-PDF, we found that the N-PDF could be well-fitted with one or two log-normal distributions. These fitting results provided an alternative density structure for molecular clouds from a conventional picture. We investigated the column density, dense molecular cloud cores, and radio continuum source distributions in each cloud and found that the N-PDF shape was less correlated with the star-forming activity over a whole cloud. Furthermore, we found that the log-normal N-PDF parameters obtained from the fitting showed two impressive features. First, the log-normal distribution at the low-density part had the same mean column density ($\sim$ 10$^{21.5}$ cm$^{-2}$) for almost all the molecular clouds. Second, the width of the log-normal distribution tended to decrease with an increasing mean density of the structures. These correlations suggest that the shape of the N-PDF reflects the relationship between the density and turbulent structure of the whole molecular cloud but is less affected by star-forming activities.

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arXiv2023

A low-mass hub-filament with double centre revealed in NGC2071-North

We present the first analysis in NGC2071-North as a resolved hub-filament featuring a double centre. This $\sim 1.5 \times 1.5$ parsec-scale filament hub contains $\sim$500 $M_\odot$. Seen from Planck, magnetic field lines may have facilitated the gathering of material at this isolated location. The energy balance analysis, supported by infalling gas signatures, reveal that these filaments are currently forming stars. Herschel 100 $μ$m emission concentrates in the hub, at IRAS 05451+0037 and LkH$α$ 316, and presents diffuse lobes and loops around them. We suggest that such a double centre could be formed, because the converging locations of filament pairs are offset, by 2.3$'$ (0.27 pc). This distance also matches the diameter of a hub-ring, seen in column density and molecular tracers, such as HCO$^+$(1$-$0) and HCN(1$-$0), that may indicate a transition and the connection between the hub and the radiating filaments. We argue that all of the three components of the emission star LkH$α$ 316 are in physical association. We find that a $\sim$0.06 pc-sized gas loop, attached to IRAS 05451+0037, can be seen at wavelengths all the way from Pan-STARRS-i to Herschel-100 $μ$m. These observations suggest that both protostars at the double hub centre are interacting with the cloud material. In our $^{13}$CO data, we do not seem to find the outflow of this region that was identified in the 80s with much lower resolution.

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arXiv2022

Distance determination of molecular clouds in the 1st quadrant of the Galactic plane using deep learning : I. Method and Results

Machine learning has been successfully applied in varied field but whether it is a viable tool for determining the distance to molecular clouds in the Galaxy is an open question. In the Galaxy, the kinematic distance is commonly employed as the distance to a molecular cloud. However, there is a problem in that for the inner Galaxy, two different solutions, the ``Near'' solution, and the ``Far'' solution, can be derived simultaneously. We attempted to construct a two-class (``Near'' or ``Far'') inference model using a Convolutional Neural Network (CNN), a form of deep learning that can capture spatial features generally. In this study, we used the CO dataset toward the 1st quadrant of the Galactic plane obtained with the Nobeyama 45-m radio telescope (l = 62-10 degree, |b| < 1 degree). In the model, we applied the three-dimensional distribution (position-position-velocity) of the 12CO (J=1-0) emissions as the main input. The dataset with ``Near'' or ``Far'' annotation was made from the HII region catalog of the infrared astronomy satellite WISE to train the model. As a result, we could construct a CNN model with a 76% accuracy rate on the training dataset. By using the model, we determined the distance to molecular clouds identified by the CLUMPFIND algorithm. We found that the mass of the molecular clouds with a distance of < 8.15 kpc identified in the 12CO data follows a power-law distribution with an index of about -2.3 in the mass range of M >10^3 Msun. Also, the detailed molecular gas distribution of the Galaxy as seen from the Galactic North pole was determined.

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arXiv2022

CARMA-NRO Orion Survey: unbiased survey of dense cores and core mass functions in Orion A

The mass distribution of dense cores is a potential key to understand the process of star formation. Applying dendrogram analysis to the CARMA-NRO Orion C$^{18}$O ($J$=1--0) data, we identify 2342 dense cores, about 22 \% of which have virial ratios smaller than 2, and can be classified as gravitationally bound cores. The derived core mass function (CMF) for bound starless cores which are not associate with protostars has a slope similar to Salpeter's initial mass function (IMF) for the mass range above 1 $M_\odot$, with a peak at $\sim$ 0.1 $M_\odot$. We divide the cloud into four parts based on the declination, OMC-1/2/3, OMC-4/5, L1641N/V380 Ori, and L1641C, and derive the CMFs in these regions. We find that starless cores with masses greater than 10 $M_\odot$ exist only in OMC-1/2/3, whereas the CMFs in OMC-4/5, L1641N, and L1641C are truncated at around 5--10 $M_\odot$. From the number ratio of bound starless cores and Class II objects in each subregion, the lifetime of bound starless cores is estimated to be 5--30 free-fall times, consistent with previous studies for other regions. In addition, we discuss core growth by mass accretion from the surrounding cloud material to explain the coincidence of peak masses between IMFs and CMFs. The mass accretion rate required for doubling the core mass within a core lifetime is larger than that of Bondi-Hoyle accretion by a factor of order 2. This implies that more dynamical accretion processes are required to grow cores.

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arXiv2022

SIRIUS Project. V. Formation of off-center ionized bubbles associated with Orion Nebula Cluster

Massive stars born in star clusters terminate star cluster formation by ionizing the surrounding gas. This process is considered to be prevalent in young star clusters containing massive stars. The Orion Nebula is an excellent example associated with a forming star cluster including several massive stars (the Orion Nebula Cluster; ONC) and a 2-pc size H{\sc ii} region (ionized bubble) opening toward the observer; however, the other side is still covered with dense molecular gas. Recent astrometric data acquired by the Gaia satellite revealed the stellar kinematics in this region. By comparing this data with star cluster formation simulation results, we demonstrate that massive stars born in the ONC center were ejected via three-body encounters. Further, orbit analysis indicates that $θ^2$ Ori A, the second massive star in this region, was ejected from the ONC center toward the observer and is now returning to the cluster center. Such ejected massive stars can form a hole in the dense molecular cloud and contribute to the formation of the 2-pc bubble. Our results demonstrate that the dynamics of massive stars are essential for the formation of star clusters and H{\sc ii} regions that are not always centered by massive stars.

astro-ph.GA↗

arXiv2022

SIRIUS Project. IV. The formation history of the Orion Nebula Cluster driven by clump mergers

The Orion Nebula Cluster (ONC) is an excellent example for understanding the formation of star clusters. Recent studies have shown that ONC has three distinct age populations and anisotropy in velocity dispersions, which are key characteristics for understanding the formation history of the ONC. In this study, we perform a smoothed-particle hydrodynamics/$N$-body simulation of star cluster formation from a turbulent molecular cloud. In this simulation, stellar orbits are integrated using a high-order integrator without gravitational softening; therefore, we can follow the collisional evolution of star clusters. We find that hierarchical formation causes episodic star formation that is observed in the ONC. In our simulation, star clusters evolve due to mergers of subclumps. The mergers bring cold gas with the clumps into the forming cluster. This enhances the star formation in the cluster centre. The dense cold gas in the cluster centre continues to form stars until the latest time. This explains the compact distribution of the youngest stars observed in the ONC. Subclump mergers also contribute to the anisotropy in the velocity dispersions and the formation of runaway stars. However, the anisotropy disappears within 0.5 Myr. The virial ratio of the cluster also increases after a merger due to the runaways. These results suggest that the ONC recently experienced a clump merger. We predict that most runaways originated from the ONC have already been found, but walkaways have not.

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arXiv2022

Cluster Formation in GGD12-15: Infall Motion with Rotation of the Natal Clump

We report results of observations of the GGD12-15 region, where cluster formation is actively taking place, using various molecular emission lines. The C18O (J= 1-0) emission line reveals a massive clump in the region with a mass of ~2800 Mo distributed over ~2 pc. The distribution of the C18O(J= 3-2) emission is similar to that of a star cluster forming therein, with an elliptical shape of ~1 pc in size. A bipolar molecular outflow driven by IRS 9Mc, a constituent star of the cluster, is blowing in a direction perpendicular to the elongated C18O (J= 3-2) distribution, covering the entire clump. There is a massive core with a radius of 0.3 pc and a mass of 530 Mo in the center of the clump. There are two velocity components around the core, which are prominent in a position-velocity (PV) diagram along the major axis of the clump. In addition, a PV diagram along the minor axis of the clump, which is parallel to the outflow, shows a velocity gradient opposite to that of the outflow. The velocity structure strongly indicates the infalling motion of the clump. Comparison of the observational data with a simple model of infalling oblate clumps indicates that the clump is undergoing gravitational contraction with rotation.

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