Explore the vast range of titles available.

FEEDBACK is a SOFIA (Stratospheric Observatory for Infrared Astronomy) legacy program dedicated to study the interaction of massive stars with their environment. It performs a survey of 11 galactic high mass star-forming regions in the 158 m (1.9 THz) line of [C ii] and the 63 m (4.7 THz) line of [O i]. We employ the 14 pixel Low Frequency Array and 7 pixel High Frequency Array upGREAT heterodyne instrument to spectrally resolve (0.24 MHz) these far-infrared fine structure lines. With a total observing time of 96h, we will cover ∼6700 arcmin2 at 14 1) angular resolution for the [C ii] line and 6 3 for the [O i] line. The observations started in spring 2019 (Cycle 7). Our aim is to understand the dynamics in regions dominated by different feedback processes from massive stars such as stellar winds, thermal expansion, and radiation pressure, and to quantify the mechanical energy injection and radiative heating efficiency. This is an important science topic because feedback of massive stars on their environment regulates the physical conditions and sets the emission characteristics in the interstellar medium (ISM), influences the star formation activity through molecular cloud dissolution and compression processes, and drives the evolution of the ISM in galaxies. The [C ii] line provides the kinematics of the gas and is one of the dominant cooling lines of gas for low to moderate densities and UV fields. The [O i] line traces warm and high-density gas, excited in photodissociations regions with a strong UV field or by shocks. The source sample spans a broad range in stellar characteristics from single OB stars, to small groups of O stars, to rich young stellar clusters, to ministarburst complexes. It contains well-known targets such as Aquila, the Cygnus X region, M16, M17, NGC7538, NGC6334, Vela, and W43 as well as a selection of H ii region bubbles, namely RCW49, RCW79, and RCW120. These [C ii] maps, together with the less explored [O i] 63 m line, provide an outstanding database for the community. They will be made publically available and will trigger further studies and follow-up observations.

Hi-GAL, the Herschel infrared Galactic Plane Survey, is an Open Time Key Project of theHerschel Space Observatory. It will make an unbiased photometric survey of the inner Galactic plane by mapping a2° 2 ° wide strip in the longitude range∣l∣ < 60° ∣ l ∣ < 60 ° in five wavebands between 70 μm and 500 μm. The aim of Hi-GAL is to detect the earliest phases of the formation of molecular clouds and high-mass stars and to use the optimum combination ofHerschelwavelength coverage, sensitivity, mapping strategy, and speed to deliver a homogeneous census of star-forming regions and cold structures in the interstellar medium. The resulting representative samples will yield the variation of source temperature, luminosity, mass and age in a wide range of Galactic environments at all scales from massive YSOs in protoclusters to entire spiral arms, providing an evolutionary sequence for the formation of intermediate and high-mass stars. This information is essential to the formulation of a predictive global model of the role of environment and feedback in regulating the star-formation process. Such a model is vital to understanding star formation on galactic scales and in the early universe. Hi-GAL will also provide a science legacy for decades to come with incalculable potential for systematic and serendipitous science in a wide range of astronomical fields, enabling the optimum use of future major facilities such asJWSTand ALMA.

Submillimeter continuum emission traces high molecular column densities and, thus, dense cloud regions in which new stars are forming. Surveys of the Galactic plane in such emission have the potential of delivering an unbiased view of high-mass star formation throughout the Milky Way. Here we present the scope, current status and first results of ATLASGAL, an ongoing survey of the Galactic plane using the Large APEX Bolometer Camera (LABOCA) on the Atacama Pathfinder Experiment (APEX) telescope at the Chajnantor plateau in Chile. Aimed at mapping 360 square degrees at 870 μm, with a uniform sensitivity of 50 mJy/beam, this survey will provide the first unbiased sample of cold dusty clumps in the Galaxy at submillimeter wavelengths. These will be targets for molecular line follow-up observations and high resolution studies with ALMA and the EVLA.

We show how the expansion of classical Galactic Hii regions can trigger massive-star formation via the collect & collapse process. We give examples of this process at work. We suggest that it also works in a turbulent medium.

Various physical processes are believed to trigger star formation on the borders of Galactic HII regions. Among these, the collect & collapse process is particularly attractive as it allows the formation of massive objects (single stars or clusters). In order to identify specific cases of this way of triggering star formation we are carrying out a multi-wavelength study of Galactic HII regions that exhibit signposts of massive-star formation at their borders. Hereby, we present two typical examples of such sources and discuss the results in the framework of the collect and collapse process, which seems to be at work as the major triggering agent in these two cases.

Aims. Massive stars impact their surrounding initiating star-formation along their photo-dissociation region. Once the HII region is formed it is unclear if and how the second generation of stars impacts its aspect and evolution. Methods. We performed high spectral resolution (R ~ 23400) Ha Fabry-Perot observations in five fields covering the Galactic HII region NGC 7538 and lead profiles multi-gaussian fitting to extract the parameters as peak intensity, width and velocity. We then analyse the kinematics of the ionised gas building kinematic diagrams and second order structure functions for every field. Results. The observations reveal a general blue-shifted ionised gas flow larger than 11 km s-1 in NGC 7538, consistent with previous studies. Profiles originating from features that are dark in Ha due to extinction or from outside the region show velocity dispersion larger than the one typically found for the Warm Interstellar Medium. The analysis of kinematic diagrams and second-order structure functions reveals non-thermal motions attributed to turbulence and large-scale velocity gradients. In the direction of the HII region itself the turbulence seems to be shock-dominated, with a characteristic scale length between ~ 0.72 and 1.46 pc. In this context, we propose that the kinematics of the central part of the region could be explained by the superposition of the outflow coming from IRS1 and a wind bow shock formed ahead IRS6.

Despite recent progress, the question of what regulates the star formation efficiency in galaxies remains one of the most debated problems in astrophysics. According to the dominant picture, star formation (SF) is regulated by turbulence and feedback, and the SFE is 1-2% per local free-fall time. In an alternate scenario, the SF rate in galactic disks is linearly proportional to the mass of dense gas above a critical density threshold. We aim to discriminate between these two pictures thanks to high-resolution observations tracing dense gas and young stellar objects (YSOs) for a comprehensive sample of 49 nearby massive SF complexes out to d < 3 kpc in the Galactic disk. We use data from CAFFEINE, a 350/450 \\(\\mu\\)m survey with APEX/ArTéMiS of the densest portions of all southern molecular clouds, in combination with Herschel data to produce column density maps at 8\" resolution. Our maps are free of saturation and resolve the structure of dense gas and the typical 0.1 pc width of molecular filaments at 3 kpc, which is impossible with Herschel data alone. Coupled with SFR estimates derived from Spitzer observations of the YSO content of the same clouds, this allows us to study the dependence of the SFE with density in the CAFFEINE clouds. We also combine our findings with existing SFE measurements in nearby clouds to extend our analysis down to lower column densities. Our results suggest that the SFE does not increase with density above the critical threshold and support a scenario in which the SFE in dense gas is approximately constant. However, the SFE measurements traced by Class I YSOs in nearby clouds are more inconclusive, since they are consistent with both the presence of a density threshold and a dependence on density above the threshold. Overall, we suggest that the SFE in dense gas is primarily governed by the physics of filament fragmentation into protostellar cores.

Clouds more massive than about \\(10^5\\) M\\(_\\odot\\) are potential sites of massive cluster formation. Studying the properties of such clouds in the early stages of their evolution offers an opportunity to test various cluster formation processes. We make use of CO, Herschel, and UKIDSS observations to study one such cloud, G148.24+00.41. Our results show the cloud to be of high mass (\\(\\sim\\) \\(1.1\\times10^5\\) M\\(_\\odot\\)), low dust temperature (\\(\\sim\\) 14.5 K), nearly circular (projected radius \\(\\sim\\) 26 pc), and gravitationally bound with a dense gas fraction of \\(\\sim 18\\)% and a density profile with a power-law index of \\(\\sim -1.5\\). Comparing its properties with those of nearby molecular clouds, we find that G148.24+00.41 is comparable to the Orion-A molecular cloud in terms of mass, size, and dense gas fraction. From our analyses, we find that the central area of the cloud is actively forming protostars and is moderately fractal with a Q-value of \\(\\sim\\) 0.66. We also find evidence of global mass-segregation in the cloud, with a degree of mass-segregation (\\(\\Lambda_{MSR}) \\approx3.2\\). We discuss these results along with the structure and compactness of the cloud, the spatial and temporal distribution of embedded stellar population, and their correlation with the cold dust distribution, in the context of high-mass cluster formation. Comparing our results with models of star cluster formation, we conclude that the cloud has the potential to form a cluster in the mass range \\(\\sim\\) 2000--3000 M\\(_\\odot\\) through dynamical hierarchical collapse and assembly of both gas and stars.

Numerical simulations predict that clumps (\\(\\)1 pc) should form stars at high efficiency to produce bound star clusters. We conducted a statistical study of 17 nearby cluster-forming clumps to examine the star formation rate and gas mass surface density relations (i.e. \\(_SFR\\) vs. \\(_gas\\)) at the clump scale. Using near-infrared point sources and Herschel dust continuum analysis, we obtained the radius, age, and stellar mass for most clusters in the ranges 0.5\\(-\\)1.6 pc, 0.5\\(-\\)1.5 Myr, 40\\(-\\)500 M\\(_\\), respectively, and also found that they are associated with \\(_gas\\) values ranging from 80\\(-\\)600 M\\(_\\) pc\\(^-2\\). We obtained the best-fit scaling relations as \\(_SFR\\) \\(\\) \\(_gas^1.46\\) and \\(_SFR\\) \\(\\) \\((_gas/t_ff)^0.80\\) for the studied sample of clumps. Comparing our results with existing scaling relations at cloud and extragalactic scales, we found that while the power-law exponent obtained in this work is similar to those found at these scales, the star formation rate surface densities are relatively higher for similar gas mass surface densities. From this work, we obtained instantaneous median star formation efficiency (SFE) and efficiency per free-fall time (\\(_ff\\)) of \\(\\)20% and \\(\\)13%, respectively, for the studied clumps. We discuss the cause of the obtained high SFE and \\(_ff\\) in the studied clumps and also discuss the results in the context of bound cluster formation within molecular clouds. We conclude that our results do not favour a universal scaling law with a constant value of \\(_ff\\) in star-forming systems across different scales.

Context. Filaments are ubiquitous in the Galaxy, and they host star formation. Detecting them in a reliable way is therefore key towards our understanding of the star formation process. Aims. We explore whether supervised machine learning can identify filamentary structures on the whole Galactic plane. Methods. We used two versions of UNet-based networks for image segmentation.We used H2 column density images of the Galactic plane obtained with Herschel Hi-GAL data as input data. We trained the UNet-based networks with skeletons (spine plus branches) of filaments that were extracted from these images, together with background and missing data masks that we produced. We tested eight training scenarios to determine the best scenario for our astrophysical purpose of classifying pixels as filaments. Results. The training of the UNets allows us to create a new image of the Galactic plane by segmentation in which pixels belonging to filamentary structures are identified. With this new method, we classify more pixels (more by a factor of 2 to 7, depending on the classification threshold used) as belonging to filaments than the spine plus branches structures we used as input. New structures are revealed, which are mainly low-contrast filaments that were not detected before.We use standard metrics to evaluate the performances of the different training scenarios. This allows us to demonstrate the robustness of the method and to determine an optimal threshold value that maximizes the recovery of the input labelled pixel classification. Conclusions. This proof-of-concept study shows that supervised machine learning can reveal filamentary structures that are present throughout the Galactic plane. The detection of these structures, including low-density and low-contrast structures that have never been seen before, offers important perspectives for the study of these filaments.