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39 results on '"Leurini, S."'

1. OGHReS: Star formation in the Outer Galaxy ($\ell = 250^\circ$-$280^\circ$)

Author

Urquhart, J. S., König, C., Colombo, D., Karska, A., Wyrowski, F., Menten, K. M., Moore, T. J. T., Brand, J., Elia, D., Giannetti, A., Leurini, S., Figueira, M., Lee, M. -Y., and Dumke, M.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

We have used data from the Outer Galaxy High-Resolution Survey (OGHReS) to refine the velocities, distances, and physical properties of a large sample of 3584 clumps detected in far infrared/submillimetre emission in the HiGAL survey located in the $\ell = 250^\circ-280^\circ$ region of the Galactic plane. Using $^{12}$CO and $^{13}$CO spectra, we have determined reliable velocities to 3412 clumps (95% of the sample). In comparison to the velocities from the HiGAL catalogue, we find good agreement for 80% of the sample (within 5 km/s). Using the higher resolution and sensitivity of OGHReS has allowed us to correct the velocity for 632 clumps and provide velocities for 687 clumps for which no velocity had been previously allocated. The velocities are used with a rotation curve to refine the distances to the clumps and to calculate the clumps' properties using a distance-dependent gas-to-dust ratio. We have determined reliable physical parameters for 3200 outer Galaxy dense clumps (~90% of the HiGAL sources in the region). We find a trend of decreasing luminosity-to-mass ratio with increasing Galactocentric distance, suggesting the star formation efficiency is lower in the outer Galaxy or that it is resulting in more lower mass stars than in the inner Galaxy. We also find a similar surface density for protostellar clumps located in the inner and outer Galaxy, revealing that the surface density requirements for star formation are the same across the Galactic disc., Comment: 15 pages, 13 figures. Accepted for publication by MNRAS

Published
2024
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2. Density distributions, magnetic field structures and fragmentation in high-mass star formation

Author

Beuther, H., Gieser, C., Soler, J. D., Zhang, Q., Rao, R., Semenov, D., Henning, Th., Pudritz, R., Peters, T., Klaassen, P., Beltran, M. T., Palau, A., Moeller, T., Johnston, K. G., Zinnecker, H., Urquhart, J., Kuiper, R., Ahmadi, A., Sanchez-Monge, A., Feng, S., Leurini, S., and Ragan, S. E.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

Methods: Observing the large pc-scale Stokes I mm dust continuum emission with the IRAM 30m telescope and the intermediate-scale (<0.1pc) polarized submm dust emission with the Submillimeter Array toward a sample of 20 high-mass star-forming regions allows us to quantify the dependence of the fragmentation behaviour of these regions depending on the density and magnetic field structures. Results: We infer density distributions n~r^{-p} of the regions with typical power-law slopes p around ~1.5. There is no obvious correlation between the power-law slopes of the density structures on larger clump scales (~1pc) and the number of fragments on smaller core scales (<0.1pc). Comparing the large-scale single-dish density profiles to those derived earlier from interferometric observations at smaller spatial scales, we find that the smaller-scale power-law slopes are steeper, typically around ~2.0. The flattening toward larger scales is consistent with the star-forming regions being embedded in larger cloud structures that do not decrease in density away from a particular core. Regarding the magnetic field, for several regions it appears aligned with filamentary structures leading toward the densest central cores. Furthermore, we find different polarization structures with some regions exhibiting central polarization holes whereas other regions show polarized emission also toward the central peak positions. Nevertheless, the polarized intensities are inversely related to the Stokes I intensities. We estimate magnetic field strengths between ~0.2 and ~4.5mG, and we find no clear correlation between magnetic field strength and the fragmentation level of the regions. Comparison of the turbulent to magnetic energies shows that they are of roughly equal importance in this sample. The mass-to-flux ratios range between ~2 and ~7, consistent with collapsing star-forming regions., Comment: Accepted for Astronomy & Astrophysics, 14 pages, 14 figures plus appendices, also download option at https://www2.mpia-hd.mpg.de/homes/beuther/papers.html

Published
2023

3. Infall and Outflow Towards High-mass Starless Clump Candidates

Author

Pillai, T. G. S., Urquhart, J. S., Leurini, S., Zhang, Q., Traficante, A., Colombo, D., Wang, K., Gomez, L., and Wyrowski, F.

Subjects
Astrophysics - Astrophysics of Galaxies, Astrophysics - Solar and Stellar Astrophysics
Abstract

The evolutionary sequence for high-mass star formation starts with massive starless clumps that go on to form protostellar, young stellar objects and then compact HII regions. While there are many examples of the three later stages, the very early stages have proved to be elusive. We follow-up a sample of 110 mid-infrared dark clumps selected from the ATLASGAL catalogue with the IRAM telescope in an effort to identify a robust sample of massive starless clumps. We have used the HCO+ (1-0) and HNC (1-0) transitions to identify clumps associated with infall motion and the SiO (2-1) transition to identity outflow candidates. We have found blue asymmetric line profile in 65% of the sample, and have measured the infall velocities and mass infall rates (0.6-$36 \times 10^{-3}$ Msun/yr) for 33 of these clumps. We find a trend for the mass infall rate decreasing with an increase of bolometric luminosity to clump mass i.e. star formation within the clumps evolves. Using the SiO 2-1 line, we have identified good outflow candidates. Combining the infall and outflow tracers reveals that 67% of quiescent clumps are already undergoing gravitational collapse or are associated with star formation; these clumps provide us with our best opportunity to determined the initial conditions and study the earliest stages of massive star formation. Finally, we provide an overview of a systematic high-resolution ALMA study of quiescent clumps selected that allows us to develop a detailed understanding of earliest stages and their subsequent evolution., Comment: 10 pages and 7 figures

Published
2023
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4. Kinematics and stability of high-mass protostellar disk candidates at sub-arcsecond resolution -- Insights from the IRAM NOEMA large program CORE

Author

Ahmadi, Aida, Beuther, H., Bosco, F., Gieser, C., Suri, S., Mottram, J. C., Kuiper, R., Henning, Th., Sánchez-Monge, Á., Linz, H., Pudritz, R. E., Semenov, D., Winters, J. M., Möller, T., Beltrán, M. T., Csengeri, T., Galván-Madrid, R., Johnston, K. G., Keto, E., Klaassen, P. D., Leurini, S., Longmore, S. N., Lumsden, S. L., Maud, L. T., Moscadelli, L., Palau, A., Peters, T., Ragan, S. E., Urquhart, J. S., Zhang, Q., and Zinnecker, H.

Subjects
Astrophysics - Astrophysics of Galaxies, Astrophysics - Solar and Stellar Astrophysics
Abstract

The fragmentation mode of high-mass molecular clumps and the accretion processes that form the most massive stars ($M\gtrsim 8M_\odot$) are still not well understood. To this end, we have undertaken a large observational program (CORE) making use of interferometric observations from the Northern Extended Millimetre Array (NOEMA) for a sample of 20 luminous ($L>10^4L_\odot$) protostellar objects in the 1.37 mm wavelength regime in both continuum and line emission, reaching $\sim$0.4" resolution (800 au at 2 kpc). Using the dense gas tracer CH$_3$CN, we find velocity gradients across 13 cores perpendicular to the directions of bipolar molecular outflows, making them excellent disk candidates. Specific angular momentum ($j$) radial profiles are on average $\sim10^{-3}$ km /s pc and follow $j \propto r^{1.7}$, consistent with a poorly resolved rotating and infalling envelope/disk model. Fitting the velocity profiles with a Keplerian model, we find protostellar masses in the range of $\sim 10-25$ $M_\odot$. Modelling the level population of CH$_3$CN lines, we present temperature maps and find median gas temperatures in the range $70-210$ K. We create Toomre $Q$ maps to study the stability of the disks and find almost all (11 of 13) disk candidates to be prone to fragmentation due to gravitational instabilities at the scales probed by our observations. In particular, disks with masses greater than $\sim10-20\%$ of the mass of their host (proto)stars are Toomre unstable, and more luminous protostellar objects tend to have disks that are more massive and hence more prone to fragmentation. Our finings show that most disks around high-mass protostars are prone to disk fragmentation early in their formation due to their high disk to stellar mass ratio. This impacts the accretion evolution of high-mass protostars which will have significant implications for the formation of the most massive stars., Comment: 27 pages, 12 figures, 6 appendices - accepted for publication in Astronomy and Astrophysics

Published
2023
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5. The SOUL view of IRAS20126+4104. Kinematics and variability of the H$_2$ jet from a massive protostar

Author

Massi, F., Garatti, A. Caratti o, Cesaroni, R., Sridharan, T. K., Ghose, E., Pinna, E., Beltrán, M. T., Leurini, S., Moscadelli, L., Sanna, A., Agapito, G., Briguglio, R., Christou, J., Esposito, S., Mazzoni, T., Miller, D., Plantet, C., Power, J., Puglisi, A., Rossi, F., Rothberg, B., Taylor, G., and Veillet, C.

Subjects
Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract

We exploit the increased sensitivity of the recently installed AO SOUL at the LBT to obtain new high-spatial-resolution NIR images of the massive young stellar object IRAS20126+4104 and its outflow. We aim to derive the jet proper motions and kinematics, as well as to study its photometric variability by combining the novel performances of SOUL together with previous NIR images. We used both broad-band ($K_{s}$, $K'$) and narrow-band (Br$\gamma$, H2) observations from a number of NIR cameras (UKIRT/UFTI,SUBARU/CIAO,TNG/NICS,LBT/PISCES,and LBT/LUCI1) to derive maps of the continuum and the H$_2$ emission in the 2.12 $\mu$m line. Three sets of images, obtained with AO systems (CIAO,2003; FLAO,2012; SOUL,2020), allowed us to derive the proper motions of a large number of H$_2$ knots along the jet. Photometry from all images was used to study the jet variability. We derived knot proper motions in the range of 1.7-20.3 mas yr$^{-1}$ (i.e. 13-158 km s$^{-1}$ at 1.64 kpc, avg. outflow tangential velocity $\sim$ 80 km s$^{-1}$). The derived knot dynamical age spans a $\sim$ 200-4000 yr interval. A ring-like H$_2$ feature near the protostar location exhibits peculiar kinematics and may represent the outcome of a wide-angle wind impinging on the outflow cavity. Both H$_2$ geometry and velocities agree with those inferred from proper motions of the H$_2$O masers, located at a smaller distance from the protostar. Although the total H$_2$ line emission from the knots does not exhibit time variations at a $\widetilde{>}$ 0.3 mag level, we have found a clear continuum flux variation (radiation scattered by the dust in the cavity opened by the jet) which is anti-correlated between the blue-shifted and red-shifted lobes and may be periodic (with a period of $\sim$ 12-18 yr). We suggest that the continuum variability might be related to inner-disc oscillations which have also caused the jet precession., Comment: 26 pages, 22 figures, 2 mpeg files, accepted by Astronomy & Astrophysics

Published
2023
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6. The Star Formation Rate of the Milky Way as seen by Herschel

Author

Elia, D., Molinari, S., Schisano, E., Soler, J. D., Merello, M., Russeil, D., Veneziani, M., Zavagno, A., Noriega-Crespo, A., Olmi, L., Benedettini, M., Hennebelle, P., Klessen, R. S., Leurini, S., Paladini, R., Pezzuto, S., Traficante, A., Eden, D. J., Martin, P. G., Sormani, M., Coletta, A., Colman, T., Plume, R., Maruccia, Y., Mininni, C., and Liu, S. J.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

We present a new derivation of the Milky Way's current star formation rate (SFR) based on the data of the Hi-GAL Galactic plane survey. We estimate the distribution of the SFR across the Galactic plane from the star-forming clumps identified in the Hi-GAL survey and calculate the total SFR from the sum of their contributions. The estimate of the global SFR amounts to $2.0 \pm 0.7$~M$_{\odot}$~yr$^{-1}$, of which $1.7 \pm 0.6$~M$_{\odot}$~yr$^{-1}$ coming from clumps with reliable heliocentric distance assignment. This value is in general agreement with estimates found in the literature of last decades. The profile of SFR density averaged in Galactocentric rings is found to be qualitatively similar to others previously computed, with a peak corresponding to the Central Molecular Zone and another one around Galactocentric radius $R_\mathrm{gal} \sim 5$~kpc, followed by an exponential decrease as $\log(\Sigma_\mathrm{SFR}/[\mathrm{M}_\odot~\mathrm{yr}^{-1}~\mathrm{kpc}^{-2}])=a\,R_\mathrm{gal}/[\mathrm{kpc}]+b $, with $a=-0.28 \pm 0.01$. In this regard, the fraction of SFR produced within and outside the Solar circle is 84\% and 16\%, respectively; the fraction corresponding to the far outer Galaxy ($R_\mathrm{gal} > 13.5$~kpc) is only 1\%. We also find that, for $R_\mathrm{gal}>3$~kpc, our data follow a power law as a function of density, similarly to the Kennicutt-Schmidt relation. Finally, we compare the distribution of the SFR density across the face-on Galactic plane and those of median parameters, such as temperature, luminosity/mass ratio and bolometric temperature, describing the evolutionary stage of Hi-GAL clumps. We found no clear correlation between the SFR and the clump evolutionary stage., Comment: To be published in ApJ

Published
2022
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7. The SEDIGISM survey: Molecular cloud morphology. II. Integrated source properties

Author

Neralwar, K. R., Colombo, D., Duarte-Cabral, A., Urquhart, J. S., Mattern, M., Wyrowski, F., Menten, K. M., Barnes, P., Sanchez-Monge, A., Rigby, A. J., Mazumdar, P., Eden, D., Csengeri, T., Dobbs, C. L., Veena, V. S., Neupane, S., Henning, T., Schuller, F., Leurini, S., Wienen, M., Yang, A. Y., Ragan, S. E., Medina, S., and Nguyen-Luong, Q.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

The Structure, Excitation, and Dynamics of the Inner Galactic InterStellar Medium (SEDIGISM) survey has produced high (spatial and spectral) resolution $^{13}$CO (2-1) maps of the Milky Way. It has allowed us to investigate the molecular interstellar medium in the inner Galaxy at an unprecedented level of detail and characterise it into molecular clouds. In a previous paper, we have classified the SEDIGISM clouds into four morphologies. However, how the properties of the clouds vary for these four morphologies is not well understood. Here, we use the morphological classification of SEDIGISM clouds to find connections between the cloud morphologies, their integrated properties, and their location on scaling relation diagrams. We observe that ring-like clouds show the most peculiar properties, having, on average, higher masses, sizes, aspect ratios and velocity dispersions compared to other morphologies. We speculate that this is related to the physical mechanisms that regulate their formation and evolution, for example, turbulence from stellar feedback can often results in the creation of bubble-like structures. We also see a trend of morphology with virial parameter whereby ring-like, elongated, clumpy and concentrated clouds have virial parameters in a decreasing order. Our findings provide a foundation for a better understanding of the molecular cloud behaviour based on their measurable properties., Comment: Accepted for publication in A&A. 28 pages (17 of Appendices), 32 figures, 6 tables

Published
2022
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8. The SEDIGISM survey: Molecular cloud morphology. I. Classification and star formation

Author

Neralwar, K. R., Colombo, D., Duarte-Cabral, A., Urquhart, J. S., Mattern, M., Wyrowski, F., Menten, K. M., Barnes, P., Sanchez-Monge, A., Beuther, H., Rigby, A. J., Mazumdar, P., Eden, D., Csengeri, T., Dobbs, C. L., Veena, V. S., Neupane, S., Henning, T., Schuller, F., Leurini, S., Wienen, M., Yang, A. Y., Ragan, S. E., Medina, S., and Nguyen-Luong, Q.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

We present one of the very first extensive classifications of a large sample of molecular clouds based on their morphology. This is achieved using a recently published catalogue of 10663 clouds obtained from the first data release of the SEDIGISM survey. The clouds are classified into four different morphologies by visual inspection and using an automated algorithm -- J plots. The visual inspection also serves as a test for the J plots algorithm, as this is the first time it has been used on molecular gas. Generally, it has been found that the structure of molecular clouds is highly filamentary and our observations indeed verify that most of our molecular clouds are elongated structures. Based on our visual classification of the 10663 SEDIGISM clouds, 15% are ring-like, 57% are elongated, 15% are concentrated and 10% are clumpy clouds. The remaining clouds do not belong to any of these morphology classes and are termed unclassified. We compare the SEDIGISM molecular clouds with structures identified through other surveys, i.e. ATLASGAL elongated structures and the bubbles from Milky Way Project (MWP). We find that many of the ATLASGAL and MWP structures are velocity coherent. ATLASGAL elongated structures overlap with ~ 21% of the SEDIGISM elongated structures (elongated and clumpy clouds) and MWP bubbles overlap with ~ 25% of the SEDIGISM ring-like clouds. We also analyse the star-formation associated with different cloud morphologies using two different techniques. The first technique examines star formation efficiency (SFE) and the dense gas fraction (DGF), based on SEDIGISM clouds and ATLASGAL clumps data. The second technique uses the high-mass star formation (HMSF) threshold for molecular clouds. The results indicate that clouds with ring-like and clumpy morphologies show a higher degree of star formation., Comment: Accepted for publication in A&A. 40 pages (26 of Appendices), 55 figures, 13 tables. The updated SEDIGISM cloud catalogue, containing cloud morphology, will be available as part of the SEDIGISM database

Published
2022
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9. NIR jets from a clustered region of massive star formation: Morphology and composition in the IRAS 18264-1152 region

Author

Silva, A. R. Costa, Fedriani, R., Tan, J. C., Garatti, A. Caratti o, Ramsay, S., Rosero, V., Cosentino, G., Gorai, P., and Leurini, S.

Subjects
Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract

Massive stars form deeply embedded in their parental clouds, making it challenging to directly observe these stars and their immediate environments. It is known that accretion and ejection processes are intrinsically related, thus observing massive protostellar outflows can provide crucial information about the processes governing massive star formation close to the central engine. We aim to probe the IRAS 18264-1152 (G19.88-0.53) high-mass star-forming complex in the near infrared (NIR) through its molecular hydrogen (H2) jets to analyse the morphology and composition of the line emitting regions and to compare with other outflow tracers. We observed the H2 NIR jets via K-band (1.9-2.5um) observations obtained with the integral field units VLT/SINFONI and VLT/KMOS. SINFONI provides the highest NIR angular resolution achieved so far for the central region (~0.2''). We compared the geometry of the NIR outflows with that of the associated molecular outflow probed by CO (2-1) emission mapped with SMA. We identify nine point sources. Four of these display a rising continuum in the K-band and are BrG emitters, revealing that they are young, potentially jet-driving sources. The spectro-imaging analysis focusses on the H2 jets, for which we derived visual extinction, temperature, column density, area, and mass. The intensity, velocity, and excitation maps based on H2 emission strongly support the existence of a protostellar cluster, with at least two (and up to four) different large-scale outflows. The literature is in agreement with the outflow morphology found here. We derived a stellar density of ~4000 stars pc^-3. Our study reveals the presence of several outflows driven by young sources from a forming cluster of young, massive stars. The derived stellar number density together with the geometry of the outflows suggest that stars can form in a relatively ordered manner in this cluster., Comment: 23 pages, 14 figures. Published in A&A. Updated to correct typos and match proofs

Published
2021
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10. ATLASGAL -- Evolutionary trends in high-mass star formation

Author

Urquhart, J. S., Wells, M. R. A., Pillai, T., Leurini, S., Giannetti, A., Moore, T. J. T., Thompson, M. A., Figura, C., Colombo, D., Yang, A. Y., Koenig, C., Wyrowski, F., Menten, K. M., Rigby, A. J., Eden, D. J., and Ragan, S. E.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

ATLASGAL is a 870-mircon dust survey of 420 square degrees of the inner Galactic plane and has been used to identify ~10 000 dense molecular clumps. Dedicated follow-up observations and complementary surveys are used to characterise the physical properties of these clumps, map their Galactic distribution and investigate the evolutionary sequence for high-mass star formation. The analysis of the ATLASGAL data is ongoing: we present an up-to-date version of the catalogue. We have classified 5007 clumps into four evolutionary stages (quiescent, protostellar, young stellar objects and HII regions) and find similar numbers of clumps in each stage, suggesting a similar lifetime. The luminosity-to-mass (L/M) ratio curve shows a smooth distribution with no significant kinks or discontinuities when compared to the mean values for evolutionary stages indicating that the star-formation process is continuous and that the observational stages do not represent fundamentally different stages or changes in the physical mechanisms involved. We compare the evolutionary sample with other star-formation tracers (methanol and water masers, extended green objects and molecular outflows) and find that the association rates with these increases as a function of evolutionary stage, confirming that our classification is reliable. This also reveals a high association rate between quiescent sources and molecular outflows, revealing that outflows are the earliest indication that star formation has begun and that star formation is already ongoing in many of the clumps that are dark even at 70 micron., Comment: Accepted for publication in MNRAS. Consists of 20 pages, 15 figures, 8 table. The complete tables will be available from CDS and upon request

Published
2021
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11. OGHReS: Large-scale filaments in the outer Galaxy

Author

Colombo, D., König, C., Urquhart, J. S., Wyrowski, F., Mattern, M., Menten, K. M., Lee, M. -Y., Brand, J., Wienen, M., Mazumdar, P., Schuller, F., and Leurini, S.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

Filaments are a ubiquitous morphological feature of the molecular interstellar medium and are identified as sites of star formation. In recent years, more than 100 large-scale filaments (with a length $>10$\,pc) have been observed in the inner Milky Way. As they appear linked to Galactic dynamics, studying those structures represents an opportunity to link kiloparsec-scale phenomena to the physics of star formation, which operates on much smaller scales. In this letter, we use newly acquired Outer Galaxy High Resolution Survey (OGHReS) $^{12}$CO(2-1) data to demonstrate that a significant number of large-scale filaments are present in the outer Galaxy as well. The 37 filaments identified appear tightly associated with inter-arm regions. In addition, their masses and linear masses are, on average, one order of magnitude lower than similar-sized molecular filaments located in the inner Galaxy, showing that Milky Way dynamics is able to create very elongated features in spite of the lower gas supply in the Galactic outskirts., Comment: 5 pages (+ appendices, 9 pages), 8 figures, 1 table, accepted for publication in A&A Letters

Published
2021
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12. Astronomical source finding services for the CIRASA visual analytic platform

Author

Riggi, S., Bordiu, C., Vitello, F., Tudisco, G., Sciacca, E., Magro, D., Sortino, R., Pino, C., Molinaro, M., Benedettini, M., Leurini, S., Bufano, F., Raciti, M., and Becciani, U.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Statistics - Computation, Statistics - Machine Learning
Abstract

Innovative developments in data processing, archiving, analysis, and visualization are nowadays unavoidable to deal with the data deluge expected in next-generation facilities for radio astronomy, such as the Square Kilometre Array (SKA) and its precursors. In this context, the integration of source extraction and analysis algorithms into data visualization tools could significantly improve and speed up the cataloguing process of large area surveys, boosting astronomer productivity and shortening publication time. To this aim, we are developing a visual analytic platform (CIRASA) for advanced source finding and classification, integrating state-of-the-art tools, such as the CAESAR source finder, the ViaLactea Visual Analytic (VLVA) and Knowledge Base (VLKB). In this work, we present the project objectives and the platform architecture, focusing on the implemented source finding services., Comment: 16 pages, 6 figures

Published
2021

13. Disk fragmentation in high-mass star formation. High-resolution observations towards AFGL 2591-VLA 3

Author

Suri, S., Beuther, H., Gieser, C., Ahmadi, A., Sánchez-Monge, Á., Winters, J. M., Linz, H., Henning, Th., Beltrán, M. T., Bosco, F., Cesaroni, R., Csengeri, T., Feng, S., Hoare, M. G., Johnston, K. G., Klaasen, P., Kuiper, R., Leurini, S., Longmore, S., Lumsden, S., Maud, L., Moscadelli, L., Möller, T., Palau, A., Peters, T., Pudritz, R. E., Ragan, S. E., Semenov, D., Schilke, P., Urquhart, J. S., Wyrowski, F., and Zinnecker, H.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

Increasing evidence suggests that, similar to their low-mass counterparts, high-mass stars form through a disk-mediated accretion process. At the same time, formation of high-mass stars still necessitates high accretion rates, and hence, high gas densities, which in turn can cause disks to become unstable against gravitational fragmentation. We study the kinematics and fragmentation of the disk around the high-mass star forming region AFGL 2591-VLA 3 which was hypothesized to be fragmenting based on the observations that show multiple outflow directions. We use a new set of high-resolution (0.19 arcsec) IRAM/NOEMA observations at 843 micron towards VLA 3 which allow us to resolve its disk, characterize the fragmentation, and study its kinematics. In addition to the 843 micron continuum emission, our spectral setup targets warm dense gas and outflow tracers such as HCN, HC$_3$N and SO$_2$, as well as vibrationally excited HCN lines. The high resolution continuum and line emission maps reveal multiple fragments with subsolar masses within the inner 1000 AU of VLA 3. Furthermore, the velocity field of the inner disk observed at 843 micron shows a similar behavior to that of the larger scale velocity field studied in the CORE project at 1.37 mm. We present the first observational evidence for disk fragmentation towards AFGL 2591-VLA 3, a source that was thought to be a single high-mass core. While the fragments themselves are low-mass, the rotation of the disk is dominated by the protostar with a mass of 10.3$\pm 1.8~M_{\odot}$. These data also show that NOEMA Band 4 can obtain the highest currently achievable spatial resolution at (sub-)mm wavelengths in observations of strong northern sources., Comment: 16 pages, 11 figures, Accepted for publication in A&A

Published
2021
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14. Density distributions, magnetic field structures, and fragmentation in high-mass star formation

Author

German Research Foundation, Consejo Nacional de Ciencia y Tecnología (México), Universidad Nacional Autónoma de México, European Commission, Ministerio de Ciencia, Innovación y Universidades (España), Ministerio de Ciencia e Innovación (España), Agencia Estatal de Investigación (España), European Space Agency, European Research Council, Beuther, Henrik, Gieser, Caroline, Soler, Juan Diego, Zhang, Qizhou, Rao, Ramprasad, Semenov, D., Henning, Thomas, Pudritz, R., Peters, T., Klaassen, P., Beltrán, María Teresa, Palau, Aina, Möller, Thomas, Johnston, K. G., Zinnecker, Hans, Urquhart, J., Kuiper, Rolf, Ahmadi, Aida, Sánchez-Monge, Álvaro, Feng, Siyi, Leurini, S., Ragan, Sarah, German Research Foundation, Consejo Nacional de Ciencia y Tecnología (México), Universidad Nacional Autónoma de México, European Commission, Ministerio de Ciencia, Innovación y Universidades (España), Ministerio de Ciencia e Innovación (España), Agencia Estatal de Investigación (España), European Space Agency, European Research Council, Beuther, Henrik, Gieser, Caroline, Soler, Juan Diego, Zhang, Qizhou, Rao, Ramprasad, Semenov, D., Henning, Thomas, Pudritz, R., Peters, T., Klaassen, P., Beltrán, María Teresa, Palau, Aina, Möller, Thomas, Johnston, K. G., Zinnecker, Hans, Urquhart, J., Kuiper, Rolf, Ahmadi, Aida, Sánchez-Monge, Álvaro, Feng, Siyi, Leurini, S., and Ragan, Sarah

Abstract

[Context] The fragmentation of high-mass star-forming regions depends on a variety of physical parameters, including density, the magnetic field, and turbulent gas properties., [Aims] We evaluate the importance of the density and magnetic field structures in relation to the fragmentation properties during high-mass star formation., [Results] Based on the IRAM 30 m data, we infer density distributions n ∝ r−p of the regions with typical power-law slopes p around ~1.5. There is no obvious correlation between the power-law slopes of the density structures on larger clump scales (~1 pc) and the number of fragments on smaller core scales (<0.1 pc). Comparing the large-scale single-dish density profiles to those derived earlier from interferometric observations at smaller spatial scales, we find that the smaller-scale power-law slopes are steeper, typically around ~2.0. The flattening toward larger scales is consistent with the star-forming regions being embedded in larger cloud structures that do not decrease in density away from a particular core. The magnetic fields of several regions appear to be aligned with filamentary structures that lead toward the densest central cores. Furthermore, we find different polarization structures; some regions exhibit central polarization holes, whereas other regions show polarized emission also toward the central peak positions. Nevertheless, the polarized intensities are inversely related to the Stokes I intensities, following roughly a power-law slope of ∝ SI−0.62. We estimate magnetic field strengths between ~0.2 and ~4.5 mG, and we find no clear correlation between magnetic field strength and the fragmentation level of the regions. A comparison of the turbulent to magnetic energies shows that they are of roughly equal importance in this sample. The mass-to-flux ratios range between ~2 and ~7, consistent with collapsing star-forming regions., [Conclusions] Finding no clear correlations between the present-day large-scale density structure, the magnetic field strength, and the smaller-scale fragmentation properties of the regions, indicates that the fragmentation of high-mass star-forming regions may not be affected strongly by the initial density profiles and magnetic field properties. However, considering the limited evolutionary range and spatial scales of the presented CORE analysis, future research directions should include density structure analysis of younger regions that better resemble the initial conditions, as well as connecting the observed intermediate-scale magnetic field structure with the larger-scale magnetic fields of the parental molecular clouds.

Published
2024

16. Density distributions, magnetic field structures, and fragmentation in high-mass star formation

Author

Beuther, H., primary, Gieser, C., additional, Soler, J. D., additional, Zhang, Q., additional, Rao, R., additional, Semenov, D., additional, Henning, Th., additional, Pudritz, R., additional, Peters, T., additional, Klaassen, P., additional, Beltrán, M. T., additional, Palau, A., additional, Möller, T., additional, Johnston, K. G., additional, Zinnecker, H., additional, Urquhart, J., additional, Kuiper, R., additional, Ahmadi, A., additional, Sánchez-Monge, Á., additional, Feng, S., additional, Leurini, S., additional, and Ragan, S. E., additional

Published
2024
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17. OGHReS: star formation in the outer galaxy (ℓ = 250°–280°)

Author

Urquhart, J S, primary, König, C, additional, Colombo, D, additional, Karska, A, additional, Wyrowski, F, additional, Menten, K M, additional, Moore, T J T, additional, Brand, J, additional, Elia, D, additional, Giannetti, A, additional, Leurini, S, additional, Figueira, M, additional, Lee, M -Y, additional, and Dumke, M, additional

Published
2023
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18. OGHReS: star formation in the outer galaxy (ℓ = 250°–280°).

Author

Urquhart, J S, König, C, Colombo, D, Karska, A, Wyrowski, F, Menten, K M, Moore, T J T, Brand, J, Elia, D, Giannetti, A, Leurini, S, Figueira, M, Lee, M -Y, and Dumke, M

Subjects
STAR formation, GALAXY formation, LOW mass stars, DENSITY of stars, SUBMILLIMETER astronomy
Abstract

We have used data from the Outer Galaxy High-Resolution Survey (OGHReS) to refine the velocities, distances, and physical properties of a large sample of 3584 clumps detected in far-infrared/submillimetre emission in the Hi-GAL survey located in the ℓ = 250°–280° region of the Galactic plane. Using 12CO and 13CO spectra, we have determined reliable velocities to 3412 clumps (95 per cent of the sample). In comparison to the velocities from the Hi-GAL catalogue, we find good agreement for 80 per cent of the sample (within 5 km s−1). Using the higher resolution and sensitivity of OGHReS has allowed us to correct the velocity for 632 clumps and provide velocities for 687 clumps for which no velocity had been previously allocated. The velocities are used with a rotation curve to refine the distances to the clumps and to calculate the clumps' properties using a distance-dependent gas-to-dust ratio. We have determined reliable physical parameters for 3200 outer Galaxy dense clumps (∼90 per cent of the Hi-GAL sources in the region). We find a trend of decreasing luminosity-to-mass ratio with increasing Galactocentric distance, suggesting the star formation efficiency is lower in the outer Galaxy or that it is resulting in more lower mass stars than in the inner Galaxy. We also find a similar surface density for protostellar clumps located in the inner and outer Galaxy, revealing that the surface density requirements for star formation are the same across the Galactic disc. [ABSTRACT FROM AUTHOR]

Published
2024
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19. Kinematics and stability of high-mass protostellar disk candidates at sub-arcsecond resolution? Insights from the IRAM NOEMA large programme CORE

Author

Ahmadi, A., primary, Beuther, H., additional, Bosco, F., additional, Gieser, C., additional, Suri, S., additional, Mottram, J. C., additional, Kuiper, R., additional, Henning, T., additional, Sánchez-Monge, Á., additional, Linz, H., additional, Pudritz, R. E., additional, Semenov, D., additional, Winters, J. M., additional, Möller, T., additional, Beltrán, M. T., additional, Csengeri, T., additional, Galván-Madrid, R., additional, Johnston, K. G., additional, Keto, E., additional, Klaassen, P. D., additional, Leurini, S., additional, Longmore, S. N., additional, Lumsden, S. L., additional, Maud, L. T., additional, Moscadelli, L., additional, Palau, A., additional, Peters, T., additional, Ragan, S. E., additional, Urquhart, J. S., additional, Zhang, Q., additional, and Zinnecker, H., additional

Published
2023
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21. The SOUL view of IRAS 20126+4104

Author

Massi, F., primary, Caratti o Garatti, A., additional, Cesaroni, R., additional, Sridharan, T. K., additional, Ghose, E., additional, Pinna, E., additional, Beltrán, M. T., additional, Leurini, S., additional, Moscadelli, L., additional, Sanna, A., additional, Agapito, G., additional, Briguglio, R., additional, Christou, J., additional, Esposito, S., additional, Mazzoni, T., additional, Miller, D., additional, Plantet, C., additional, Power, J., additional, Puglisi, A., additional, Rossi, F., additional, Rothberg, B., additional, Taylor, G., additional, and Veillet, C., additional

Published
2023
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22. Infall and outflow towards high-mass starless clump candidates

Author

Pillai, T.G.S., Urquhart, J.S., Leurini, S., Zhang, Q., Traficante, A., Colombo, D., Wang, K., Gomez, L., Wyrowski, F., Pillai, T.G.S., Urquhart, J.S., Leurini, S., Zhang, Q., Traficante, A., Colombo, D., Wang, K., Gomez, L., and Wyrowski, F.

Abstract

The evolutionary sequence for high-mass star formation starts with massive starless clumps that go on to form protostellar, young stellar objects and then compact H II regions. While there are many examples of the three later stages, the very early stages have proved to be elusive. We follow-up a sample of 110 mid-infrared dark clumps selected from the ATLASGAL catalogue with the IRAM telescope in an effort to identify a robust sample of massive starless clumps. We have used the HCO+ and HNC (1-0) transitions to identify clumps associated with infall motion and the SiO (2-1) transition to identity outflow candidates. We have found blue asymmetric line profile in 65 per cent of the sample, and have measured the infall velocities and mass infall rates (0.6–36 × 10−3 M⊙ yr−1) for 33 of these clumps. We find a trend for the mass infall rate decreasing with an increase of bolometric luminosity to clump mass, i.e. star formation within the clumps evolves. Using the SiO 2-1 line, we have identified good outflow candidates. Combining the infall and outflow tracers reveals that 67 per cent of quiescent clumps are already undergoing gravitational collapse or are associated with star formation; these clumps provide us with our best opportunity to determine the initial conditions and study the earliest stages of massive star formation. Finally, we provide an overview of a systematic high-resolution ALMA study of quiescent clumps selected that allows us to develop a detailed understanding of earliest stages and their subsequent evolution.

Published
2023

23. Kinematics and stability of high-mass protostellar disk candidates at sub-arcsecond resolution

Author

Ahmadi, A., Beuther, H., Bosco, F., Gieser, C., Suri, S., Mottram, J.C., Kuiper, R., Henning, T., Sanchez-Monge, A., Linz, H., Pudritz, R.E., Semenov, D., Winters, J.M., Möller, T., Beltran, M. T., Csengeri, T., Galvan-Madrid, R., Johnston, K.G., Keto, E., Klaassen, P. D., Leurini, S., Longmore, S.N., Lumsden, S.L., Maud, L.T., Moscadelli, L., Palau, A., Peters, T., Ragan, S.E., Urquhart, J.S., Zhang, Q., Zinnecker, H., Ahmadi, A., Beuther, H., Bosco, F., Gieser, C., Suri, S., Mottram, J.C., Kuiper, R., Henning, T., Sanchez-Monge, A., Linz, H., Pudritz, R.E., Semenov, D., Winters, J.M., Möller, T., Beltran, M. T., Csengeri, T., Galvan-Madrid, R., Johnston, K.G., Keto, E., Klaassen, P. D., Leurini, S., Longmore, S.N., Lumsden, S.L., Maud, L.T., Moscadelli, L., Palau, A., Peters, T., Ragan, S.E., Urquhart, J.S., Zhang, Q., and Zinnecker, H.

Abstract

Context. The fragmentation mode of high-mass molecular clumps and the accretion processes that form the most massive stars (M & 8 M) are still not well understood. A growing number of case studies have found massive young stellar objects (MYSOs) to harbour disk-like structures, painting a picture that the formation of high-mass stars may proceed through disk accretion, similar to that of lower mass stars. However, the properties of such structures have yet to be uniformly and systematically characterised. Massive disks are prone to fragmentation via gravitational instabilities due to high gas densities and accretion rates. Therefore, it is important to study the stability of such disks in order to put into context the role of disk fragmentation in setting the final stellar mass distribution in high-mass star forming regions. Aims. The aim of this work is to uniformly study the kinematic properties of a large sample of MYSOs and characterise the stability of possible circumstellar disks against gravitational fragmentation. Methods. We have undertaken a large observational program (CORE) making use of interferometric observations from the Northern Extended Millimetre Array (NOEMA) for a sample of 20 luminous (L > 104 L) protostellar objects in the 1.37 mm wavelength regime in both continuum and spectral line emission, reaching 0.400 resolution (800 au at 2 kpc). Results. We present the gas kinematics of the full sample and detect dense gas emission surrounding 15 regions within the CORE sample. Using the dense gas tracer CH3CN, we find velocity gradients across 13 cores perpendicular to the directions of bipolar molecular outflows, making them excellent disk candidates. The extent of the CH3CN emission tracing the disk candidates varies from 1800 − 8500 au. Analysing the free-fall to rotational timescales, we find that the sources are rotationally supported. The rotation profiles of some disk candidates are well described by differential rotation while for others the

Published
2023

24. Language production impairments in patients with a first episode of psychosis

Author

Gargano, G, Caletti, E, Perlini, C, Turtulici, N, Bellani, M, Bonivento, C, Garzitto, M, Siri, F, Longo, C, Bonetto, C, Cristofalo, D, Scocco, P, Semrov, E, Preti, A, Lazzarotto, L, Gardellin, F, Lasalvia, A, Ruggeri, M, Marini, A, Brambilla, P, Bertani, M, Bissoli, S, De Santi, K, Lunardi, S, Negretto, V, Poli, S, Tosato, S, Zamboni, M, Ballarin, M, De Girolamo, G, Fioritti, A, Neri, G, Pileggi, F, Rucci, P, Chiavetto, L, Scasselatti, C, Zanardini, R, Bertoldo, A, Marinelli, V, Rambaldelli, G, Bardella, S, Lamonaca, D, Lunardon, M, Magnabosco, R, Martucci, M, Nicolau, S, Nifosi, F, Pavanati, M, Rossi, M, Piazza, C, Piccione, G, Sala, A, Sale, A, Stefani, B, Zotos, S, Balbo, M, Boggian, I, Ceccato, E, Dall'Agnola, R, Girotto, B, Goss, C, Leoni, R, Mai, A, Pasqualini, A, Roccato, S, Rossi, A, Strizzolo, S, Urbani, A, Aldi, F, Bianchi, B, Cappellari, P, Conti, R, De Battisti, L, Lazzarin, E, Merlin, S, Migliorini, G, Pozzan, T, Sarto, L, Visona, S, Brazzoli, A, Campi, A, Carmagnani, R, Giambelli, S, Gianella, A, Lunardi, L, Madaghiele, D, Maestrelli, P, Paiola, L, Posteri, E, Viola, L, Zamberlan, V, Zenari, M, Zanoni, M, Bonadonna, G, Bonomo, M, Santonastaso, P, Cremonese, C, Veronese, A, Anderle, P, Angelozzi, A, Baron, I, Candeago, E, Castelli, F, Chieco, M, Di Costanzo, E, Derossi, M, Doriguzzi, M, Galvano, O, Lattanzi, M, Lezzi, R, Marcato, M, Marcolin, A, Marini, F, Matranga, M, Scalabrin, D, Zucchetto, M, Zadro, F, Austoni, G, Bianco, M, Bordino, F, Dario, F, De Risio, A, Gatto, A, Grana, S, Favero, E, Franceschini, A, Friederici, S, Marangon, V, Pascolo, M, Ramon, L, Zambolin, S, Riolo, R, Buffon, A, Di Bortolo, E, Fortin, S, Matarrese, F, Mogni, S, Codemo, N, Russi, A, Silvestro, A, Turella, E, Viel, P, Dominoni, A, Andreose, L, Boemio, M, Bressan, L, Cabbia, A, Canesso, E, Cian, R, Dal Piccol, C, Pasqua, M, Di Prisco, A, Mantellato, L, Luison, M, Morgante, S, Santi, M, Sacillotto, M, Scabbio, M, Sponga, P, Sguotto, M, Stach, F, Vettorato, M, Martinello, G, Dassie, F, Marino, S, Cibiniel, L, Masetto, I, Cabianca, O, Valente, A, Caberlotto, L, Passoni, A, Flumian, P, Daniel, L, Gion, M, Stanziale, S, Alborino, F, Bortolozzo, V, Bacelle, L, Bicciato, L, Basso, D, Navaglia, F, Manoni, F, Ercolin, M, Giubilini, F, Imbesi, M, Leuci, E, Mazzi, F, Anelli, S, Amore, M, Bigi, L, Britta, W, Anna, G, Bonatti, U, Borziani, M, Crosato, S, Fabris, I, Galluccio, R, Galeotti, M, Gozzi, M, Greco, V, Guagnini, E, Pagani, S, Maccherozzi, S, Malvasi, R, Marchi, F, Melato, E, Mazzucchi, E, Marzullo, F, Pellegrini, P, Petrolini, N, Volta, P, Bonara, F, Brusamonti, E, Croci, R, Flamia, I, Fontana, F, Losi, R, Marchioro, R, Raffaini, L, Ruju, L, Saginario, A, Tondelli, M, Marrama, D, Bernardelli, L, Bonacini, F, Florindo, A, Merli, M, Nappo, P, Sola, L, Tondelli, O, Tonna, M, Torre, M, Tosatti, M, Venturelli, G, Zampolla, D, Bernardi, A, Cavalli, C, Cigala, L, Ciraudo, C, Di Bari, A, Ferri, L, Gombi, F, Leurini, S, Mandatelli, E, Maccaferri, S, Oroboncoide, M, Pisa, B, Ricci, C, Poggi, E, Zurlini, C, Malpeli, M, Colla, R, Teodori, E, Vecchia, L, D'Andrea, R, Trenti, T, Paolini, P, Carpeggiani, P, Ghigi, D, Gagliostro, M, Pratelli, M, Antonelli, A, Battistini, L, Bellini, F, Bonini, E, Capelli, C, Didomizio, C, Drei, C, Fucci, G, Gualandi, A, Grazia, M, Losi, A, Mazzoni, F, Marangoni, D, Monna, G, Morselli, M, Oggioni, A, Oprandi, S, Paganelli, W, Passerini, M, Piscitelli, M, Reggiani, G, Rossi, G, Salvatori, F, Trasforini, S, Uslenghi, C, Veggetti, S, Bartolucci, G, Baruffa, R, Bertelli, R, Borghi, L, Ciavarella, P, Paltrinieri, E, Rizzardi, F, Serra, P, Suzzi, D, Arienti, P, Aureli, F, Avanzi, R, Callegari, V, Corsino, A, Host, P, Michetti, R, Rizzo, F, Simoncelli, P, Soldati, E, Succi, E, Bertozzi, M, Canetti, E, Cavicchioli, L, Ceccarelli, E, Cenni, S, Marzola, G, Gallina, V, Leoni, C, Olivieri, A, Piccolo, E, Ravagli, S, Russo, R, Tedeschini, D, Verenini, M, Abram, W, Granata, V, Curcio, A, Guerra, G, Granini, S, Natali, L, Montanari, E, Pasi, F, Ventura, U, Valenti, S, Francesca, M, Farneti, R, Ravagli, P, Floris, R, Maroncelli, O, Volpones, G, Casali, D, Miceli, M, Bencini, A, Cellini, M, De Biase, L, Barbara, L, Charles, L, Pratesi, C, Tanini, A, Loparrino, R, Ulivelli, C, Cussoto, C, Dei, N, Fumanti, E, Pantani, M, Zeloni, G, Bellini, R, Cellesi, R, Dorigo, N, Gulli, P, Ialeggio, L, Pisanu, M, Rinaldi, G, Konze, A, Cocchi, A, Meneghelli, A, Frova, M, Monzani, E, Zanobio, A, Malagoli, M, Pagani, R, Barbera, S, Morganti, C, Amade, E, Brambilla, V, Montanari, A, Caterina, G, Lopez, C, Marocchi, A, Moletta, A, Sberna, M, Cascio, M, Scarone, S, Gargano G., Caletti E., Perlini C., Turtulici N., Bellani M., Bonivento C., Garzitto M., Siri F. M., Longo C., Bonetto C., Cristofalo D., Scocco P., Semrov E., Preti A., Lazzarotto L., Gardellin F., Lasalvia A., Ruggeri M., Marini A., Brambilla P., Bertani M. E., Bissoli S., De Santi K., Lunardi S., Negretto V., Poli S., Tosato S., Zamboni M. G., Ballarin M., De Girolamo G., Fioritti A., Neri G., Pileggi F., Rucci P., Chiavetto L. B., Scasselatti C., Zanardini R., Bertoldo A., Marinelli V., Rambaldelli G., Bardella S., Lamonaca D., Lunardon M., Magnabosco R., Martucci M., Nicolau S., Nifosi F., Pavanati M., Rossi M., Piazza C., Piccione G., Sala A., Sale A., Stefani B., Zotos S., Balbo M., Boggian I., Ceccato E., Dall'Agnola R., Girotto B., Goss C., Leoni R., Mai A., Pasqualini A., Roccato S., Rossi A., Strizzolo S., Urbani A., Aldi F., Bianchi B., Cappellari P., Conti R., De Battisti L., Lazzarin E., Merlin S., Migliorini G., Pozzan T., Sarto L., Visona S., Brazzoli A., Campi A., Carmagnani R., Giambelli S., Gianella A., Lunardi L., Madaghiele D., Maestrelli P., Paiola L., Posteri E., Viola L., Zamberlan V., Zenari M., Zanoni M., Bonadonna G., Bonomo M., Santonastaso P., Cremonese C., Veronese A., Anderle P., Angelozzi A., Baron I. A. G., Candeago E. B. F., Castelli F., Chieco M., Di Costanzo E., Derossi M., Doriguzzi M., Galvano O., Lattanzi M., Lezzi R., Marcato M., Marcolin A., Marini F., Matranga M., Scalabrin D., Zucchetto M., Zadro F., Austoni G., Bianco M., Bordino F., Dario F., De Risio A., Gatto A., Grana S., Favero E., Franceschini A., Friederici S., Marangon V., Pascolo M., Ramon L., Zambolin S., Riolo R., Buffon A., Di Bortolo E., Fortin S., Matarrese F., Mogni S., Codemo N., Russi A., Silvestro A., Turella E., Viel P., Dominoni A., Andreose L., Boemio M., Bressan L., Cabbia A., Canesso E., Cian R., Dal Piccol C., Pasqua M. M. D., Di Prisco A., Mantellato L., Luison M., Morgante S., Santi M., Sacillotto M., Scabbio M., Sponga P., Sguotto M., Stach F., Vettorato M., Martinello G., Dassie F., Marino S., Cibiniel L., Masetto I., Cabianca O., Valente A., Caberlotto L., Passoni A., Flumian P., Daniel L., Gion M., Stanziale S., Alborino F., Bortolozzo V., Bacelle L., Bicciato L., Basso D., Navaglia F., Manoni F., Ercolin M., Giubilini F., Imbesi M., Leuci E., Mazzi F., Anelli S., Amore M., Bigi L., Britta W., Anna G. B., Bonatti U., Borziani M., Crosato S., Fabris I., Galluccio R., Galeotti M., Gozzi M., Greco V., Guagnini E., Pagani S., Maccherozzi S., Malvasi R., Marchi F., Melato E., Mazzucchi E., Marzullo F., Pellegrini P., Petrolini N., Volta P., Bonara F., Brusamonti E., Croci R., Flamia I., Fontana F., Losi R., Marchioro R., Raffaini L., Ruju L., Saginario A., Tondelli M., Marrama D., Bernardelli L., Bonacini F., Florindo A., Merli M., Nappo P., Sola L., Tondelli O., Tonna M., Torre M., Tosatti M., Venturelli G., Zampolla D., Bernardi A., Cavalli C., Cigala L., Ciraudo C., Di Bari A., Ferri L., Gombi F., Leurini S., Mandatelli E., Maccaferri S., Oroboncoide M., Pisa B., Ricci C., Poggi E., Zurlini C., Malpeli M., Colla R., Teodori E., Vecchia L., D'Andrea R., Trenti T., Paolini P., Carpeggiani P., Ghigi D., Gagliostro M., Pratelli M., Antonelli A., Battistini L., Bellini F., Bonini E., Capelli C. B. R., DiDomizio C., Drei C., Fucci G., Gualandi A., Grazia M. R., Losi A. M., Mazzoni F. M. P., Marangoni D., Monna G., Morselli M., Oggioni A., Oprandi S., Paganelli W., Passerini M., Piscitelli M., Reggiani G., Rossi G., Salvatori F., Trasforini S., Uslenghi C., Veggetti S., Bartolucci G., Baruffa R., Bertelli R., Borghi L., Ciavarella P., Paltrinieri E., Rizzardi F., Serra P., Suzzi D., Arienti P., Aureli F., Avanzi R., Callegari V., Corsino A., Host P., Michetti R., Rizzo F., Simoncelli P., Soldati E., Succi E., Bertozzi M., Canetti E., Cavicchioli L., Ceccarelli E., Cenni S., Marzola G., Gallina V., Leoni C., Olivieri A., Piccolo E., Ravagli S., Russo R., Tedeschini D., Verenini M., Abram W., Granata V., Curcio A., Guerra G., Granini S., Natali L., Montanari E., Pasi F., Ventura U., Valenti S., Francesca M., Farneti R., Ravagli P., Floris R., Maroncelli O., Volpones G., Casali D., Miceli M., Bencini A., Cellini M., De Biase L., Barbara L., Charles L., Pratesi C., Tanini A., Loparrino R., Ulivelli C., Cussoto C., Dei N., Fumanti E., Pantani M., Zeloni G., Bellini R., Cellesi R., Dorigo N., Gulli P., Ialeggio L., Pisanu M., Rinaldi G., Konze A., Cocchi A., Meneghelli A., Frova M., Monzani E., Zanobio A., Malagoli M., Pagani R., Barbera S., Morganti C., Amade E. S., Brambilla V., Montanari A., Caterina G., Lopez C., Marocchi A., Moletta A., Sberna M., Cascio M. T., Scarone S., Gargano, G, Caletti, E, Perlini, C, Turtulici, N, Bellani, M, Bonivento, C, Garzitto, M, Siri, F, Longo, C, Bonetto, C, Cristofalo, D, Scocco, P, Semrov, E, Preti, A, Lazzarotto, L, Gardellin, F, Lasalvia, A, Ruggeri, M, Marini, A, Brambilla, P, Bertani, M, Bissoli, S, De Santi, K, Lunardi, S, Negretto, V, Poli, S, Tosato, S, Zamboni, M, Ballarin, M, De Girolamo, G, Fioritti, A, Neri, G, Pileggi, F, Rucci, P, Chiavetto, L, Scasselatti, C, Zanardini, R, Bertoldo, A, Marinelli, V, Rambaldelli, G, Bardella, S, Lamonaca, D, Lunardon, M, Magnabosco, R, Martucci, M, Nicolau, S, Nifosi, F, Pavanati, M, Rossi, M, Piazza, C, Piccione, G, Sala, A, Sale, A, Stefani, B, Zotos, S, Balbo, M, Boggian, I, Ceccato, E, Dall'Agnola, R, Girotto, B, Goss, C, Leoni, R, Mai, A, Pasqualini, A, Roccato, S, Rossi, A, Strizzolo, S, Urbani, A, Aldi, F, Bianchi, B, Cappellari, P, Conti, R, De Battisti, L, Lazzarin, E, Merlin, S, Migliorini, G, Pozzan, T, Sarto, L, Visona, S, Brazzoli, A, Campi, A, Carmagnani, R, Giambelli, S, Gianella, A, Lunardi, L, Madaghiele, D, Maestrelli, P, Paiola, L, Posteri, E, Viola, L, Zamberlan, V, Zenari, M, Zanoni, M, Bonadonna, G, Bonomo, M, Santonastaso, P, Cremonese, C, Veronese, A, Anderle, P, Angelozzi, A, Baron, I, Candeago, E, Castelli, F, Chieco, M, Di Costanzo, E, Derossi, M, Doriguzzi, M, Galvano, O, Lattanzi, M, Lezzi, R, Marcato, M, Marcolin, A, Marini, F, Matranga, M, Scalabrin, D, Zucchetto, M, Zadro, F, Austoni, G, Bianco, M, Bordino, F, Dario, F, De Risio, A, Gatto, A, Grana, S, Favero, E, Franceschini, A, Friederici, S, Marangon, V, Pascolo, M, Ramon, L, Zambolin, S, Riolo, R, Buffon, A, Di Bortolo, E, Fortin, S, Matarrese, F, Mogni, S, Codemo, N, Russi, A, Silvestro, A, Turella, E, Viel, P, Dominoni, A, Andreose, L, Boemio, M, Bressan, L, Cabbia, A, Canesso, E, Cian, R, Dal Piccol, C, Pasqua, M, Di Prisco, A, Mantellato, L, Luison, M, Morgante, S, Santi, M, Sacillotto, M, Scabbio, M, Sponga, P, Sguotto, M, Stach, F, Vettorato, M, Martinello, G, Dassie, F, Marino, S, Cibiniel, L, Masetto, I, Cabianca, O, Valente, A, Caberlotto, L, Passoni, A, Flumian, P, Daniel, L, Gion, M, Stanziale, S, Alborino, F, Bortolozzo, V, Bacelle, L, Bicciato, L, Basso, D, Navaglia, F, Manoni, F, Ercolin, M, Giubilini, F, Imbesi, M, Leuci, E, Mazzi, F, Anelli, S, Amore, M, Bigi, L, Britta, W, Anna, G, Bonatti, U, Borziani, M, Crosato, S, Fabris, I, Galluccio, R, Galeotti, M, Gozzi, M, Greco, V, Guagnini, E, Pagani, S, Maccherozzi, S, Malvasi, R, Marchi, F, Melato, E, Mazzucchi, E, Marzullo, F, Pellegrini, P, Petrolini, N, Volta, P, Bonara, F, Brusamonti, E, Croci, R, Flamia, I, Fontana, F, Losi, R, Marchioro, R, Raffaini, L, Ruju, L, Saginario, A, Tondelli, M, Marrama, D, Bernardelli, L, Bonacini, F, Florindo, A, Merli, M, Nappo, P, Sola, L, Tondelli, O, Tonna, M, Torre, M, Tosatti, M, Venturelli, G, Zampolla, D, Bernardi, A, Cavalli, C, Cigala, L, Ciraudo, C, Di Bari, A, Ferri, L, Gombi, F, Leurini, S, Mandatelli, E, Maccaferri, S, Oroboncoide, M, Pisa, B, Ricci, C, Poggi, E, Zurlini, C, Malpeli, M, Colla, R, Teodori, E, Vecchia, L, D'Andrea, R, Trenti, T, Paolini, P, Carpeggiani, P, Ghigi, D, Gagliostro, M, Pratelli, M, Antonelli, A, Battistini, L, Bellini, F, Bonini, E, Capelli, C, Didomizio, C, Drei, C, Fucci, G, Gualandi, A, Grazia, M, Losi, A, Mazzoni, F, Marangoni, D, Monna, G, Morselli, M, Oggioni, A, Oprandi, S, Paganelli, W, Passerini, M, Piscitelli, M, Reggiani, G, Rossi, G, Salvatori, F, Trasforini, S, Uslenghi, C, Veggetti, S, Bartolucci, G, Baruffa, R, Bertelli, R, Borghi, L, Ciavarella, P, Paltrinieri, E, Rizzardi, F, Serra, P, Suzzi, D, Arienti, P, Aureli, F, Avanzi, R, Callegari, V, Corsino, A, Host, P, Michetti, R, Rizzo, F, Simoncelli, P, Soldati, E, Succi, E, Bertozzi, M, Canetti, E, Cavicchioli, L, Ceccarelli, E, Cenni, S, Marzola, G, Gallina, V, Leoni, C, Olivieri, A, Piccolo, E, Ravagli, S, Russo, R, Tedeschini, D, Verenini, M, Abram, W, Granata, V, Curcio, A, Guerra, G, Granini, S, Natali, L, Montanari, E, Pasi, F, Ventura, U, Valenti, S, Francesca, M, Farneti, R, Ravagli, P, Floris, R, Maroncelli, O, Volpones, G, Casali, D, Miceli, M, Bencini, A, Cellini, M, De Biase, L, Barbara, L, Charles, L, Pratesi, C, Tanini, A, Loparrino, R, Ulivelli, C, Cussoto, C, Dei, N, Fumanti, E, Pantani, M, Zeloni, G, Bellini, R, Cellesi, R, Dorigo, N, Gulli, P, Ialeggio, L, Pisanu, M, Rinaldi, G, Konze, A, Cocchi, A, Meneghelli, A, Frova, M, Monzani, E, Zanobio, A, Malagoli, M, Pagani, R, Barbera, S, Morganti, C, Amade, E, Brambilla, V, Montanari, A, Caterina, G, Lopez, C, Marocchi, A, Moletta, A, Sberna, M, Cascio, M, Scarone, S, Gargano G., Caletti E., Perlini C., Turtulici N., Bellani M., Bonivento C., Garzitto M., Siri F. M., Longo C., Bonetto C., Cristofalo D., Scocco P., Semrov E., Preti A., Lazzarotto L., Gardellin F., Lasalvia A., Ruggeri M., Marini A., Brambilla P., Bertani M. E., Bissoli S., De Santi K., Lunardi S., Negretto V., Poli S., Tosato S., Zamboni M. G., Ballarin M., De Girolamo G., Fioritti A., Neri G., Pileggi F., Rucci P., Chiavetto L. B., Scasselatti C., Zanardini R., Bertoldo A., Marinelli V., Rambaldelli G., Bardella S., Lamonaca D., Lunardon M., Magnabosco R., Martucci M., Nicolau S., Nifosi F., Pavanati M., Rossi M., Piazza C., Piccione G., Sala A., Sale A., Stefani B., Zotos S., Balbo M., Boggian I., Ceccato E., Dall'Agnola R., Girotto B., Goss C., Leoni R., Mai A., Pasqualini A., Roccato S., Rossi A., Strizzolo S., Urbani A., Aldi F., Bianchi B., Cappellari P., Conti R., De Battisti L., Lazzarin E., Merlin S., Migliorini G., Pozzan T., Sarto L., Visona S., Brazzoli A., Campi A., Carmagnani R., Giambelli S., Gianella A., Lunardi L., Madaghiele D., Maestrelli P., Paiola L., Posteri E., Viola L., Zamberlan V., Zenari M., Zanoni M., Bonadonna G., Bonomo M., Santonastaso P., Cremonese C., Veronese A., Anderle P., Angelozzi A., Baron I. A. G., Candeago E. B. F., Castelli F., Chieco M., Di Costanzo E., Derossi M., Doriguzzi M., Galvano O., Lattanzi M., Lezzi R., Marcato M., Marcolin A., Marini F., Matranga M., Scalabrin D., Zucchetto M., Zadro F., Austoni G., Bianco M., Bordino F., Dario F., De Risio A., Gatto A., Grana S., Favero E., Franceschini A., Friederici S., Marangon V., Pascolo M., Ramon L., Zambolin S., Riolo R., Buffon A., Di Bortolo E., Fortin S., Matarrese F., Mogni S., Codemo N., Russi A., Silvestro A., Turella E., Viel P., Dominoni A., Andreose L., Boemio M., Bressan L., Cabbia A., Canesso E., Cian R., Dal Piccol C., Pasqua M. M. D., Di Prisco A., Mantellato L., Luison M., Morgante S., Santi M., Sacillotto M., Scabbio M., Sponga P., Sguotto M., Stach F., Vettorato M., Martinello G., Dassie F., Marino S., Cibiniel L., Masetto I., Cabianca O., Valente A., Caberlotto L., Passoni A., Flumian P., Daniel L., Gion M., Stanziale S., Alborino F., Bortolozzo V., Bacelle L., Bicciato L., Basso D., Navaglia F., Manoni F., Ercolin M., Giubilini F., Imbesi M., Leuci E., Mazzi F., Anelli S., Amore M., Bigi L., Britta W., Anna G. B., Bonatti U., Borziani M., Crosato S., Fabris I., Galluccio R., Galeotti M., Gozzi M., Greco V., Guagnini E., Pagani S., Maccherozzi S., Malvasi R., Marchi F., Melato E., Mazzucchi E., Marzullo F., Pellegrini P., Petrolini N., Volta P., Bonara F., Brusamonti E., Croci R., Flamia I., Fontana F., Losi R., Marchioro R., Raffaini L., Ruju L., Saginario A., Tondelli M., Marrama D., Bernardelli L., Bonacini F., Florindo A., Merli M., Nappo P., Sola L., Tondelli O., Tonna M., Torre M., Tosatti M., Venturelli G., Zampolla D., Bernardi A., Cavalli C., Cigala L., Ciraudo C., Di Bari A., Ferri L., Gombi F., Leurini S., Mandatelli E., Maccaferri S., Oroboncoide M., Pisa B., Ricci C., Poggi E., Zurlini C., Malpeli M., Colla R., Teodori E., Vecchia L., D'Andrea R., Trenti T., Paolini P., Carpeggiani P., Ghigi D., Gagliostro M., Pratelli M., Antonelli A., Battistini L., Bellini F., Bonini E., Capelli C. B. R., DiDomizio C., Drei C., Fucci G., Gualandi A., Grazia M. R., Losi A. M., Mazzoni F. M. P., Marangoni D., Monna G., Morselli M., Oggioni A., Oprandi S., Paganelli W., Passerini M., Piscitelli M., Reggiani G., Rossi G., Salvatori F., Trasforini S., Uslenghi C., Veggetti S., Bartolucci G., Baruffa R., Bertelli R., Borghi L., Ciavarella P., Paltrinieri E., Rizzardi F., Serra P., Suzzi D., Arienti P., Aureli F., Avanzi R., Callegari V., Corsino A., Host P., Michetti R., Rizzo F., Simoncelli P., Soldati E., Succi E., Bertozzi M., Canetti E., Cavicchioli L., Ceccarelli E., Cenni S., Marzola G., Gallina V., Leoni C., Olivieri A., Piccolo E., Ravagli S., Russo R., Tedeschini D., Verenini M., Abram W., Granata V., Curcio A., Guerra G., Granini S., Natali L., Montanari E., Pasi F., Ventura U., Valenti S., Francesca M., Farneti R., Ravagli P., Floris R., Maroncelli O., Volpones G., Casali D., Miceli M., Bencini A., Cellini M., De Biase L., Barbara L., Charles L., Pratesi C., Tanini A., Loparrino R., Ulivelli C., Cussoto C., Dei N., Fumanti E., Pantani M., Zeloni G., Bellini R., Cellesi R., Dorigo N., Gulli P., Ialeggio L., Pisanu M., Rinaldi G., Konze A., Cocchi A., Meneghelli A., Frova M., Monzani E., Zanobio A., Malagoli M., Pagani R., Barbera S., Morganti C., Amade E. S., Brambilla V., Montanari A., Caterina G., Lopez C., Marocchi A., Moletta A., Sberna M., Cascio M. T., and Scarone S.

Abstract

Language production has often been described as impaired in psychiatric diseases such as in psychosis. Nevertheless, little is known about the characteristics of linguistic difficulties and their relation with other cognitive domains in patients with a first episode of psychosis (FEP), either affective or non-affective. To deepen our comprehension of linguistic profile in FEP, 133 patients with FEP (95 non-affective, FEP-NA; 38 affective, FEP-A) and 133 healthy controls (HC) were assessed with a narrative discourse task. Speech samples were systematically analyzed with a well-established multilevel procedure investigating both micro- (lexicon, morphology, syntax) and macro-linguistic (discourse coherence, pragmatics) levels of linguistic processing. Executive functioning and IQ were also evaluated. Both linguistic and neuropsychological measures were secondarily implemented with a machine learning approach in order to explore their predictive accuracy in classifying participants as FEP or HC. Compared to HC, FEP patients showed language production difficulty at both micro- and macro-linguistic levels. As for the former, FEP produced shorter and simpler sentences and fewer words per minute, along with a reduced number of lexical fillers, compared to HC. At the macro-linguistic level, FEP performance was impaired in local coherence, which was paired with a higher percentage of utterances with semantic errors. Linguistic measures were not correlated with any neuropsychological variables. No significant differences emerged between FEP-NA and FEP-A (p≥0.02, after Bonferroni correction). Machine learning analysis showed an accuracy of group prediction of 76.36% using language features only, with semantic variables being the most impactful. Such a percentage was enhanced when paired with clinical and neuropsychological variables. Results confirm the presence of language production deficits already at the first episode of the illness, being such impairment not related to ot

Published
2022

25. The Star Formation Rate of the Milky Way as Seen by Herschel

Author

Elia, D., primary, Molinari, S., additional, Schisano, E., additional, Soler, J. D., additional, Merello, M., additional, Russeil, D., additional, Veneziani, M., additional, Zavagno, A., additional, Noriega-Crespo, A., additional, Olmi, L., additional, Benedettini, M., additional, Hennebelle, P., additional, Klessen, R. S., additional, Leurini, S., additional, Paladini, R., additional, Pezzuto, S., additional, Traficante, A., additional, Eden, D. J., additional, Martin, P. G., additional, Sormani, M., additional, Coletta, A., additional, Colman, T., additional, Plume, R., additional, Maruccia, Y., additional, Mininni, C., additional, and Liu, S. J., additional

Published
2022
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26. Language production impairments in patients with a first episode of psychosis

Author

Gargano G., Caletti E., Perlini C., Turtulici N., Bellani M., Bonivento C., Garzitto M., Siri F. M., Longo C., Bonetto C., Cristofalo D., Scocco P., Semrov E., Preti A., Lazzarotto L., Gardellin F., Lasalvia A., Ruggeri M., Marini A., Brambilla P., Bertani M. E., Bissoli S., De Santi K., Lunardi S., Negretto V., Poli S., Tosato S., Zamboni M. G., Ballarin M., De Girolamo G., Fioritti A., Neri G., Pileggi F., Rucci P., Chiavetto L. B., Scasselatti C., Zanardini R., Bertoldo A., Marinelli V., Rambaldelli G., Bardella S., Lamonaca D., Lunardon M., Magnabosco R., Martucci M., Nicolau S., Nifosi F., Pavanati M., Rossi M., Piazza C., Piccione G., Sala A., Sale A., Stefani B., Zotos S., Balbo M., Boggian I., Ceccato E., Dall'Agnola R., Girotto B., Goss C., Leoni R., Mai A., Pasqualini A., Roccato S., Rossi A., Strizzolo S., Urbani A., Aldi F., Bianchi B., Cappellari P., Conti R., De Battisti L., Lazzarin E., Merlin S., Migliorini G., Pozzan T., Sarto L., Visona S., Brazzoli A., Campi A., Carmagnani R., Giambelli S., Gianella A., Lunardi L., Madaghiele D., Maestrelli P., Paiola L., Posteri E., Viola L., Zamberlan V., Zenari M., Zanoni M., Bonadonna G., Bonomo M., Santonastaso P., Cremonese C., Veronese A., Anderle P., Angelozzi A., Baron I. A. G., Candeago E. B. F., Castelli F., Chieco M., Di Costanzo E., Derossi M., Doriguzzi M., Galvano O., Lattanzi M., Lezzi R., Marcato M., Marcolin A., Marini F., Matranga M., Scalabrin D., Zucchetto M., Zadro F., Austoni G., Bianco M., Bordino F., Dario F., De Risio A., Gatto A., Grana S., Favero E., Franceschini A., Friederici S., Marangon V., Pascolo M., Ramon L., Zambolin S., Riolo R., Buffon A., Di Bortolo E., Fortin S., Matarrese F., Mogni S., Codemo N., Russi A., Silvestro A., Turella E., Viel P., Dominoni A., Andreose L., Boemio M., Bressan L., Cabbia A., Canesso E., Cian R., Dal Piccol C., Pasqua M. M. D., Di Prisco A., Mantellato L., Luison M., Morgante S., Santi M., Sacillotto M., Scabbio M., Sponga P., Sguotto M., Stach F., Vettorato M., Martinello G., Dassie F., Marino S., Cibiniel L., Masetto I., Cabianca O., Valente A., Caberlotto L., Passoni A., Flumian P., Daniel L., Gion M., Stanziale S., Alborino F., Bortolozzo V., Bacelle L., Bicciato L., Basso D., Navaglia F., Manoni F., Ercolin M., Giubilini F., Imbesi M., Leuci E., Mazzi F., Anelli S., Amore M., Bigi L., Britta W., Anna G. B., Bonatti U., Borziani M., Crosato S., Fabris I., Galluccio R., Galeotti M., Gozzi M., Greco V., Guagnini E., Pagani S., Maccherozzi S., Malvasi R., Marchi F., Melato E., Mazzucchi E., Marzullo F., Pellegrini P., Petrolini N., Volta P., Bonara F., Brusamonti E., Croci R., Flamia I., Fontana F., Losi R., Marchioro R., Raffaini L., Ruju L., Saginario A., Tondelli M., Marrama D., Bernardelli L., Bonacini F., Florindo A., Merli M., Nappo P., Sola L., Tondelli O., Tonna M., Torre M., Tosatti M., Venturelli G., Zampolla D., Bernardi A., Cavalli C., Cigala L., Ciraudo C., Di Bari A., Ferri L., Gombi F., Leurini S., Mandatelli E., Maccaferri S., Oroboncoide M., Pisa B., Ricci C., Poggi E., Zurlini C., Malpeli M., Colla R., Teodori E., Vecchia L., D'Andrea R., Trenti T., Paolini P., Carpeggiani P., Ghigi D., Gagliostro M., Pratelli M., Antonelli A., Battistini L., Bellini F., Bonini E., Capelli C. B. R., DiDomizio C., Drei C., Fucci G., Gualandi A., Grazia M. R., Losi A. M., Mazzoni F. M. P., Marangoni D., Monna G., Morselli M., Oggioni A., Oprandi S., Paganelli W., Passerini M., Piscitelli M., Reggiani G., Rossi G., Salvatori F., Trasforini S., Uslenghi C., Veggetti S., Bartolucci G., Baruffa R., Bertelli R., Borghi L., Ciavarella P., Paltrinieri E., Rizzardi F., Serra P., Suzzi D., Arienti P., Aureli F., Avanzi R., Callegari V., Corsino A., Host P., Michetti R., Rizzo F., Simoncelli P., Soldati E., Succi E., Bertozzi M., Canetti E., Cavicchioli L., Ceccarelli E., Cenni S., Marzola G., Gallina V., Leoni C., Olivieri A., Piccolo E., Ravagli S., Russo R., Tedeschini D., Verenini M., Abram W., Granata V., Curcio A., Guerra G., Granini S., Natali L., Montanari E., Pasi F., Ventura U., Valenti S., Francesca M., Farneti R., Ravagli P., Floris R., Maroncelli O., Volpones G., Casali D., Miceli M., Bencini A., Cellini M., De Biase L., Barbara L., Charles L., Pratesi C., Tanini A., Loparrino R., Ulivelli C., Cussoto C., Dei N., Fumanti E., Pantani M., Zeloni G., Bellini R., Cellesi R., Dorigo N., Gulli P., Ialeggio L., Pisanu M., Rinaldi G., Konze A., Cocchi A., Meneghelli A., Frova M., Monzani E., Zanobio A., Malagoli M., Pagani R., Barbera S., Morganti C., Amade E. S., Brambilla V., Montanari A., Caterina G., Lopez C., Marocchi A., Moletta A., Sberna M., Cascio M. T., Scarone S., Gargano, G, Caletti, E, Perlini, C, Turtulici, N, Bellani, M, Bonivento, C, Garzitto, M, Siri, F, Longo, C, Bonetto, C, Cristofalo, D, Scocco, P, Semrov, E, Preti, A, Lazzarotto, L, Gardellin, F, Lasalvia, A, Ruggeri, M, Marini, A, Brambilla, P, Bertani, M, Bissoli, S, De Santi, K, Lunardi, S, Negretto, V, Poli, S, Tosato, S, Zamboni, M, Ballarin, M, De Girolamo, G, Fioritti, A, Neri, G, Pileggi, F, Rucci, P, Chiavetto, L, Scasselatti, C, Zanardini, R, Bertoldo, A, Marinelli, V, Rambaldelli, G, Bardella, S, Lamonaca, D, Lunardon, M, Magnabosco, R, Martucci, M, Nicolau, S, Nifosi, F, Pavanati, M, Rossi, M, Piazza, C, Piccione, G, Sala, A, Sale, A, Stefani, B, Zotos, S, Balbo, M, Boggian, I, Ceccato, E, Dall'Agnola, R, Girotto, B, Goss, C, Leoni, R, Mai, A, Pasqualini, A, Roccato, S, Rossi, A, Strizzolo, S, Urbani, A, Aldi, F, Bianchi, B, Cappellari, P, Conti, R, De Battisti, L, Lazzarin, E, Merlin, S, Migliorini, G, Pozzan, T, Sarto, L, Visona, S, Brazzoli, A, Campi, A, Carmagnani, R, Giambelli, S, Gianella, A, Lunardi, L, Madaghiele, D, Maestrelli, P, Paiola, L, Posteri, E, Viola, L, Zamberlan, V, Zenari, M, Zanoni, M, Bonadonna, G, Bonomo, M, Santonastaso, P, Cremonese, C, Veronese, A, Anderle, P, Angelozzi, A, Baron, I, Candeago, E, Castelli, F, Chieco, M, Di Costanzo, E, Derossi, M, Doriguzzi, M, Galvano, O, Lattanzi, M, Lezzi, R, Marcato, M, Marcolin, A, Marini, F, Matranga, M, Scalabrin, D, Zucchetto, M, Zadro, F, Austoni, G, Bianco, M, Bordino, F, Dario, F, De Risio, A, Gatto, A, Grana, S, Favero, E, Franceschini, A, Friederici, S, Marangon, V, Pascolo, M, Ramon, L, Zambolin, S, Riolo, R, Buffon, A, Di Bortolo, E, Fortin, S, Matarrese, F, Mogni, S, Codemo, N, Russi, A, Silvestro, A, Turella, E, Viel, P, Dominoni, A, Andreose, L, Boemio, M, Bressan, L, Cabbia, A, Canesso, E, Cian, R, Dal Piccol, C, Pasqua, M, Di Prisco, A, Mantellato, L, Luison, M, Morgante, S, Santi, M, Sacillotto, M, Scabbio, M, Sponga, P, Sguotto, M, Stach, F, Vettorato, M, Martinello, G, Dassie, F, Marino, S, Cibiniel, L, Masetto, I, Cabianca, O, Valente, A, Caberlotto, L, Passoni, A, Flumian, P, Daniel, L, Gion, M, Stanziale, S, Alborino, F, Bortolozzo, V, Bacelle, L, Bicciato, L, Basso, D, Navaglia, F, Manoni, F, Ercolin, M, Giubilini, F, Imbesi, M, Leuci, E, Mazzi, F, Anelli, S, Amore, M, Bigi, L, Britta, W, Anna, G, Bonatti, U, Borziani, M, Crosato, S, Fabris, I, Galluccio, R, Galeotti, M, Gozzi, M, Greco, V, Guagnini, E, Pagani, S, Maccherozzi, S, Malvasi, R, Marchi, F, Melato, E, Mazzucchi, E, Marzullo, F, Pellegrini, P, Petrolini, N, Volta, P, Bonara, F, Brusamonti, E, Croci, R, Flamia, I, Fontana, F, Losi, R, Marchioro, R, Raffaini, L, Ruju, L, Saginario, A, Tondelli, M, Marrama, D, Bernardelli, L, Bonacini, F, Florindo, A, Merli, M, Nappo, P, Sola, L, Tondelli, O, Tonna, M, Torre, M, Tosatti, M, Venturelli, G, Zampolla, D, Bernardi, A, Cavalli, C, Cigala, L, Ciraudo, C, Di Bari, A, Ferri, L, Gombi, F, Leurini, S, Mandatelli, E, Maccaferri, S, Oroboncoide, M, Pisa, B, Ricci, C, Poggi, E, Zurlini, C, Malpeli, M, Colla, R, Teodori, E, Vecchia, L, D'Andrea, R, Trenti, T, Paolini, P, Carpeggiani, P, Ghigi, D, Gagliostro, M, Pratelli, M, Antonelli, A, Battistini, L, Bellini, F, Bonini, E, Capelli, C, Didomizio, C, Drei, C, Fucci, G, Gualandi, A, Grazia, M, Losi, A, Mazzoni, F, Marangoni, D, Monna, G, Morselli, M, Oggioni, A, Oprandi, S, Paganelli, W, Passerini, M, Piscitelli, M, Reggiani, G, Rossi, G, Salvatori, F, Trasforini, S, Uslenghi, C, Veggetti, S, Bartolucci, G, Baruffa, R, Bertelli, R, Borghi, L, Ciavarella, P, Paltrinieri, E, Rizzardi, F, Serra, P, Suzzi, D, Arienti, P, Aureli, F, Avanzi, R, Callegari, V, Corsino, A, Host, P, Michetti, R, Rizzo, F, Simoncelli, P, Soldati, E, Succi, E, Bertozzi, M, Canetti, E, Cavicchioli, L, Ceccarelli, E, Cenni, S, Marzola, G, Gallina, V, Leoni, C, Olivieri, A, Piccolo, E, Ravagli, S, Russo, R, Tedeschini, D, Verenini, M, Abram, W, Granata, V, Curcio, A, Guerra, G, Granini, S, Natali, L, Montanari, E, Pasi, F, Ventura, U, Valenti, S, Francesca, M, Farneti, R, Ravagli, P, Floris, R, Maroncelli, O, Volpones, G, Casali, D, Miceli, M, Bencini, A, Cellini, M, De Biase, L, Barbara, L, Charles, L, Pratesi, C, Tanini, A, Loparrino, R, Ulivelli, C, Cussoto, C, Dei, N, Fumanti, E, Pantani, M, Zeloni, G, Bellini, R, Cellesi, R, Dorigo, N, Gulli, P, Ialeggio, L, Pisanu, M, Rinaldi, G, Konze, A, Cocchi, A, Meneghelli, A, Frova, M, Monzani, E, Zanobio, A, Malagoli, M, Pagani, R, Barbera, S, Morganti, C, Amade, E, Brambilla, V, Montanari, A, Caterina, G, Lopez, C, Marocchi, A, Moletta, A, Sberna, M, Cascio, M, and Scarone, S

Subjects
Language Disorders, Multidisciplinary, Comprehension, Humans, Language, Neuropsychological Tests, Psychotic Disorders, Psychosis, Language Disorder, Psychosis, Language, Cognition, Neuropsychology, Cognition, Neuropsychology, Neuropsychological Test, Settore MED/25 - Psichiatria, Human
Abstract

Language production has often been described as impaired in psychiatric diseases such as in psychosis. Nevertheless, little is known about the characteristics of linguistic difficulties and their relation with other cognitive domains in patients with a first episode of psychosis (FEP), either affective or non-affective. To deepen our comprehension of linguistic profile in FEP, 133 patients with FEP (95 non-affective, FEP-NA; 38 affective, FEP-A) and 133 healthy controls (HC) were assessed with a narrative discourse task. Speech samples were systematically analyzed with a well-established multilevel procedure investigating both micro- (lexicon, morphology, syntax) and macro-linguistic (discourse coherence, pragmatics) levels of linguistic processing. Executive functioning and IQ were also evaluated. Both linguistic and neuropsychological measures were secondarily implemented with a machine learning approach in order to explore their predictive accuracy in classifying participants as FEP or HC. Compared to HC, FEP patients showed language production difficulty at both micro- and macro-linguistic levels. As for the former, FEP produced shorter and simpler sentences and fewer words per minute, along with a reduced number of lexical fillers, compared to HC. At the macro-linguistic level, FEP performance was impaired in local coherence, which was paired with a higher percentage of utterances with semantic errors. Linguistic measures were not correlated with any neuropsychological variables. No significant differences emerged between FEP-NA and FEP-A (p≥0.02, after Bonferroni correction). Machine learning analysis showed an accuracy of group prediction of 76.36% using language features only, with semantic variables being the most impactful. Such a percentage was enhanced when paired with clinical and neuropsychological variables. Results confirm the presence of language production deficits already at the first episode of the illness, being such impairment not related to other cognitive domains. The high accuracy obtained by the linguistic set of features in classifying groups support the use of machine learning methods in neuroscience investigations.

Published
2022

27. The SEDIGISM survey: Molecular cloud morphology

Author

Neralwar, K., Colombo, D., Duarte-Cabral, A., Urquhart, J., Mattern, M., Wyrowski, F., Menten, K., Barnes, P., Sánchez-Monge, Á., Rigby, A., Mazumdar, P., Eden, D., Csengeri, T., Dobbs, C., Veena, V., Neupane, S., Henning, T., Schuller, F., Leurini, S., Wienen, M., Yang, A., Ragan, S., Medina, S., Nguyen-Luong, Q., School of Physics and Astronomy [Cardiff], Cardiff University, Astrophysique Interprétation Modélisation (AIM (UMR_7158 / UMR_E_9005 / UM_112)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Max-Planck-Institut für Radioastronomie (MPIFR), Max Planck Institute for Radio Astronomy, Universität zu Köln = University of Cologne, Astrophysics Research Institute [Liverpool] (ARI), Liverpool John Moores University (LJMU), FORMATION STELLAIRE 2020, Laboratoire d'Astrophysique de Bordeaux [Pessac] (LAB), Université de Bordeaux (UB)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), University of Tampere [Finland], INAF - Osservatorio Astronomico di Cagliari (OAC), and Istituto Nazionale di Astrofisica (INAF)

Subjects
[PHYS.ASTR.GA]Physics [physics]/Astrophysics [astro-ph]/Galactic Astrophysics [astro-ph.GA], [SDU]Sciences of the Universe [physics]
Abstract

International audience; The Structure, Excitation, and Dynamics of the Inner Galactic InterStellar Medium (SEDIGISM) survey has produced high (spatial and spectral) resolution 13 CO (2−1) maps of the Milky Way. It has allowed us to investigate the molecular interstellar medium in the inner Galaxy at an unprecedented level of detail and characterise it into molecular clouds (MCs). In a previous paper, we classified the SEDIGISM clouds into four morphologies. However, how the properties of the clouds vary for these four morphologies is not well understood. Here, we use the morphological classification of SEDIGISM clouds to find connections between the cloud morphologies, their integrated properties, and their location on scaling relation diagrams. We observe that ring-like clouds show the most peculiar properties, having, on average, higher masses, sizes, aspect ratios, and velocity dispersions, compared to other morphologies. We speculate that this is related to the physical mechanisms that regulate their formation and evolution; for example, turbulence from stellar feedback can often result in the creation of bubble-like structures. We also see a trend of morphology with the virial parameter, whereby ring-like, elongated, clumpy, and concentrated clouds have virial parameters in decreasing order. Our findings provide a foundation for a better understanding of MC behaviour, based on their measurable properties.

Published
2022

28. The SEDIGISM survey: Molecular cloud morphology. II: Integrated source properties

Author

Neralwar, K.R., Colombo, D., Duarte-Cabral, A., Urquhart, J.S., Mattern, M., Wyrowski, F., Menten, K.M., Barnes, P., Sánchez-Monge, Á., Rigby, A.J., Mazumdar, P., Eden, D., Csengeri, T., Dobbs, C. L., Veena, V. S., Neupane, S., Henning, T., Schuller, F., Leurini, S., Wienen, M., Yang, A. Y., Ragan, S.E., Medina, S., Nguyen-Luong, Q., Neralwar, K.R., Colombo, D., Duarte-Cabral, A., Urquhart, J.S., Mattern, M., Wyrowski, F., Menten, K.M., Barnes, P., Sánchez-Monge, Á., Rigby, A.J., Mazumdar, P., Eden, D., Csengeri, T., Dobbs, C. L., Veena, V. S., Neupane, S., Henning, T., Schuller, F., Leurini, S., Wienen, M., Yang, A. Y., Ragan, S.E., Medina, S., and Nguyen-Luong, Q.

Abstract

The Structure, Excitation, and Dynamics of the Inner Galactic InterStellar Medium (SEDIGISM) survey has produced high (spatial and spectral) resolution 13CO (2–1) maps of the Milky Way. It has allowed us to investigate the molecular interstellar medium in the inner Galaxy at an unprecedented level of detail and characterise it into molecular clouds. In a previous paper, we have classified the SEDIGISM clouds into four morphologies. However, how the properties of the clouds vary for these four morphologies is not well understood. Here, we use the morphological classification of SEDIGISM clouds to find connections between the cloud morphologies, their integrated properties, and their location on scaling relation diagrams. We observe that ring-like clouds show the most peculiar properties, having, on average, higher masses, sizes, aspect ratios and velocity dispersions compared to other morphologies. We speculate that this is related to the physical mechanisms that regulate their formation and evolution, for example, turbulence from stellar feedback can often results in the creation of bubble-like structures. We also see a trend of morphology with virial parameter whereby ring-like, elongated, clumpy and concentrated clouds have virial parameters in a decreasing order. Our findings provide a foundation for a better understanding of the molecular cloud behaviour based on their measurable properties.

Published
2022

29. The SEDIGISM survey: Molecular cloud morphology. I. Classification and star formation

Author

Neralwar, K.R., Colombo, D., Duarte-Cabral, A., Urquhart, J.S., Mattern, M., Wyrowski, F., Menten, K.M., Barnes, P., Sánchez-Monge, Á., Beuther, H., Rigby, A.J., Mazumdar, P., Eden, D., Csengeri, T., Dobbs, C. L., Veena, V. S., Neupane, S., Henning, T., Schuller, F., Leurini, S., Wienen, M., Yang, A. Y., Ragan, S.E., Medina, S., Nguyen-Luong, Q., Neralwar, K.R., Colombo, D., Duarte-Cabral, A., Urquhart, J.S., Mattern, M., Wyrowski, F., Menten, K.M., Barnes, P., Sánchez-Monge, Á., Beuther, H., Rigby, A.J., Mazumdar, P., Eden, D., Csengeri, T., Dobbs, C. L., Veena, V. S., Neupane, S., Henning, T., Schuller, F., Leurini, S., Wienen, M., Yang, A. Y., Ragan, S.E., Medina, S., and Nguyen-Luong, Q.

Abstract

We present one of the very first extensive classifications of a large sample of molecular clouds based on their morphology. This is achieved using a recently published catalogue of 10663 clouds obtained from the first data release of the SEDIGISM survey. The clouds are classified into four different morphologies by visual inspection and using an automated algorithm – J plots. The visual inspection also serves as a test for the J plots algorithm, as this is the first time it has been used on molecular gas. Generally, it has been found that the structure of molecular clouds is highly filamentary and our observations indeed verify that most of our molecular clouds are elongated structures. Based on our visual classification of the 10663 SEDIGISM clouds, 15% are ring-like, 57% are elongated, 15% are concentrated and 10% are clumpy clouds. The remaining clouds do not belong to any of these morphology classes and are termed unclassified. We compare the SEDIGISM molecular clouds with structures identified through other surveys, i.e. ATLASGAL elongated structures and the bubbles from Milky Way Project (MWP). We find that many of the ATLASGAL and MWP structures are velocity coherent. ATLASGAL elongated structures overlap with ≈ 21% of the SEDIGISM elongated structures (elongated and clumpy clouds) and MWP bubbles overlap with ≈ 25% of the SEDIGISM ring-like clouds. We also analyse the starformation associated with different cloud morphologies using two different techniques. The first technique examines star formation efficiency (SFE) and the dense gas fraction (DGF), based on SEDIGISM clouds and ATLASGAL clumps data. The second technique uses the high-mass star formation (HMSF) threshold for molecular clouds. The results indicate that clouds with ring-like and clumpy morphologies show a higher degree of star formation.

Published
2022

30. The evolution of temperature and density structures of OB cluster-forming molecular clumps

Author

Lin, Y., Wyrowski, F., Liu, H. B., Izquierdo, A. F., Csengeri, T., Leurini, S., Menten, K. M., Lin, Y., Wyrowski, F., Liu, H. B., Izquierdo, A. F., Csengeri, T., Leurini, S., and Menten, K. M.

Abstract

Context. OB star clusters originate from parsec-scale massive molecular clumps, while individual stars may form in less than or similar to 0.1 pc scale dense cores. The thermal properties of the clump gas are key factors governing the fragmentation process, and are closely affected by gas dynamics and feedback of forming stars. Aims. We aim to understand the evolution of temperature and density structures on the intermediate-scale (less than or similar to 0.1-1 pc) extended gas of massive clumps. This gas mass reservoir is critical for the formation of OB clusters, due to their extended inflow activities and intense thermal feedback during and after formation. Methods. We performed -0.1 pc resolution observations of multiple molecular line tracers (e.g., CH3CCH, H2CS, CH3CN, CH3OH) that cover a wide range of excitation conditions, toward a sample of eight massive clumps. The sample covers different stages of evolution, and includes infrared-weak clumps and sources that are already hosting an HII region, spanning a wide luminosity-to-mass ratio (L/M) range from similar to 1 to similar to 100 (L-circle dot/M-circle dot). Based on various radiative transfer models, we constrain the gas temperature and density structures and establish an evolutionary picture, aided by a spatially dependent virial analysis and abundance ratios of multiple species. Results. We determine temperature profiles varying in the range 30-200 K over a continuous scale, from the center of the clumps out to 0.3-0.4 pc radii. The clumps' radial gas density profiles, described by radial power laws with slopes between -0.6 and similar to-1.5, are steeper for more evolved sources, as suggested by results based on dust continuum, representing the bulk of the gas (similar to 10(4) cm(-3)), and on CH3OH lines probing the dense gas (greater than or similar to 10(6)-10(8) cm(-3)) regime. The density contrast between the dense gas and the bulk gas increases with evolution, and may be indicative of spatially

Published
2022

31. The SOUL view of IRAS 20126+4104: Kinematics and variability of the H2 jet from a massive protostar.

Author

Massi, F., Garatti, A. Caratti, Cesaroni, R., Sridharan, T. K., Ghose, E., Pinna, E., Beltrán, M. T., Leurini, S., Moscadelli, L., Sanna, A., Agapito, G., Briguglio, R., Christou, J., Esposito, S., Mazzoni, T., Miller, D., Plantet, C., Power, J., Puglisi, A., and Rossi, F.

Subjects
KINEMATICS, SOUL, RANGE of motion of joints, MASERS, PROTOSTARS, INFRARED imaging, STELLAR rotation
Abstract

Context. We exploit the increased sensitivity of the recently installed adaptive optics SOUL at the LBT to obtain new high-spatialresolution near-infrared images of the massive young stellar object IRAS20126+4104 and its outflow. Aims. We aim to derive the jet proper motions and kinematics, as well as to study its photometric variability by combining the novel performances of SOUL together with previous near-infrared images. Methods. We used both broad-band (Ks, K') and narrow-band (Br H2) observations from a number of near-infrared cameras (UKIRT/UFTI, SUBARU/CIAO, TNG/NICS, LBT/PISCES, and LBT/LUCI1) to derive maps of the continuum and the H2 emission in the 2.12 µm line. Three sets of images, obtained with adaptive optics (AO) systems (CIAO, in 2003; FLAO, in 2012; SOUL, in 2020), allowed us to derive the proper motions of a large number of H2 knots along the jet. Photometry from all images was used to study the jet variability. Results. We derived knot proper motions in the range of 1.7-20.3 mas yr-1 (i.e. 13-158 km s-1 at 1.64 kpc), implying an average outflow tangential velocity of ~80 km s-1. The derived knot dynamical age spans a ~200-4000 yr interval. A ring-like H2 feature near the protostar location exhibits peculiar kinematics and may represent the outcome of a wide-angle wind impinging on the outflow cavity. Both H2 geometry and velocities agree with those inferred from proper motions of the H2O masers, located at a smaller distance from the protostar. Although the total H2 line emission from the knots does not exhibit time variations at a >~0.3 mag level, we have found a clear continuum flux variation (radiation scattered by the dust in the cavity opened by the jet) which is anti-correlated between the blue-shifted and red-shifted lobes and may be periodic (with a period of ~12-18 yr). We suggest that the continuum variability might be related to inner-disc oscillations which have also caused the jet precession. Conclusions. Our analysis shows that multi-epoch high-spatial-resolution imaging in the near-infrared is a powerful tool to unveil the physical properties of highly embedded massive protostars. [ABSTRACT FROM AUTHOR]

Published
2023
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34. Feasibility Study of a W-band Multibeam Heterodyne Receiver for the Gregorian Focus of the Sardinia Radio Telescope

Author

Navarrini, A., primary, Olmi, L., additional, Nesti, R., additional, Ortu, P., additional, Marongiu, P., additional, Orlati, A., additional, Scalambra, A., additional, Orfei, A., additional, Roda, J., additional, Cattani, A., additional, Leurini, S., additional, Govoni, F., additional, Murgia, M., additional, Carretti, E., additional, Fierro, D., additional, and Pellizzoni, A., additional

Published
2022
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35. ATLASGAL – evolutionary trends in high-mass star formation

Author

Urquhart, J S, primary, Wells, M R A, additional, Pillai, T, additional, Leurini, S, additional, Giannetti, A, additional, Moore, T J T, additional, Thompson, M A, additional, Figura, C, additional, Colombo, D, additional, Yang, A Y, additional, König, C, additional, Wyrowski, F, additional, Menten, K M, additional, Rigby, A J, additional, Eden, D J, additional, and Ragan, S E, additional

Published
2021
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36. OGHReS: Large-scale filaments in the outer Galaxy

Author

Colombo, D., primary, König, C., additional, Urquhart, J. S., additional, Wyrowski, F., additional, Mattern, M., additional, Menten, K. M., additional, Lee, M.-Y., additional, Brand, J., additional, Wienen, M., additional, Mazumdar, P., additional, Schuller, F., additional, and Leurini, S., additional

Published
2021
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37. Disk fragmentation in high-mass star formation

Author

Suri, S., primary, Beuther, H., additional, Gieser, C., additional, Ahmadi, A., additional, Sánchez-Monge, Á., additional, Winters, J. M., additional, Linz, H., additional, Henning, Th., additional, Beltrán, M. T., additional, Bosco, F., additional, Cesaroni, R., additional, Csengeri, T., additional, Feng, S., additional, Hoare, M. G., additional, Johnston, K. G., additional, Klaassen, P., additional, Kuiper, R., additional, Leurini, S., additional, Longmore, S., additional, Lumsden, S., additional, Maud, L., additional, Moscadelli, L., additional, Möller, T., additional, Palau, A., additional, Peters, T., additional, Pudritz, R. E., additional, Ragan, S. E., additional, Semenov, D., additional, Schilke, P., additional, Urquhart, J. S., additional, Wyrowski, F., additional, and Zinnecker, H., additional

Published
2021
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38. Astronomical source finding services for the CIRASA visual analytic platform

Author

Riggi, S., primary, Bordiu, C., additional, Vitello, F., additional, Tudisco, G., additional, Sciacca, E., additional, Magro, D., additional, Sortino, R., additional, Pino, C., additional, Molinaro, M., additional, Benedettini, M., additional, Leurini, S., additional, Bufano, F., additional, Raciti, M., additional, and Becciani, U., additional

Published
2021
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39. ATLASGAL – evolutionary trends in high-mass star formation.

Author

Urquhart, J S, Wells, M R A, Pillai, T, Leurini, S, Giannetti, A, Moore, T J T, Thompson, M A, Figura, C, Colombo, D, Yang, A Y, König, C, Wyrowski, F, Menten, K M, Rigby, A J, Eden, D J, and Ragan, S E

Subjects
HIGH mass stars, STAR formation, STELLAR evolution
Abstract

ATLASGAL is an 870-µm dust survey of 420 deg2 the inner Galactic plane and has been used to identify ∼10 000 dense molecular clumps. Dedicated follow-up observations and complementary surveys are used to characterize the physical properties of these clumps, map their Galactic distribution, and investigate the evolutionary sequence for high-mass star formation. The analysis of the ATLASGAL data is ongoing: We present an up-to-date version of the catalogue. We have classified 5007 clumps into four evolutionary stages (quiescent, protostellar, young stellar objects and H  ii regions) and find similar numbers of clumps in each stage, suggesting a similar lifetime. The luminosity-to-mass (L bol/ M fwhm) ratio curve shows a smooth distribution with no significant kinks or discontinuities when compared to the mean values for evolutionary stages indicating that the star formation process is continuous and that the observational stages do not represent fundamentally different stages or changes in the physical mechanisms involved. We compare the evolutionary sample with other star formation tracers (methanol and water masers, extended green objects and molecular outflows) and find that the association rates with these increases as a function of evolutionary stage, confirming that our classification is reliable. This also reveals a high association rate between quiescent sources and molecular outflows, revealing that outflows are the earliest indication that star formation has begun and that star formation is already ongoing in many of the clumps that are dark even at 70 µm. [ABSTRACT FROM AUTHOR]

Published
2022
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