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Record W4290572372 · doi:10.1051/0004-6361/202141677

ALMA-IMF

2021· article· en· W4290572372 on OpenAlexaff
F. Motte, S. Bontemps, T. Csengeri, Y. Pouteau, F. Louvet, Amelia M. Stutz, N. Cunningham, A. López-Sepulcre, N. Brouillet, Roberto Galván-Madrid, Adam Ginsburg, L. T. Maud, A. Men’shchikov, F. Nakamura, T. Nony, Patricio Sanhueza, R. H. Álvarez-Gutiérrez, M. Armante, Tapas Baug, M. Bonfand, G. Busquet, E. Chapillon, D. Díaz-González, Manuel Fernández-López, Andrés E. Guzmán, F. Herpin, Hongli Liu, Fernando A. Olguin, A. P. M. Towner, J. Bally, Cara Battersby, J. Braine, L. Bronfman, Huei-Ru Vivien Chen, P. Dell’Ova, James Di Francesco, M. González, A. Gusdorf, P. Hennebelle, Natsuko Izumi, Isabelle Joncour, Yueh-Ning Lee, B. Leflóch, P. Lesaffre, Xing Lu, K. M. Menten, R. Mignon-Risse, J. Molet, E. Moraux, Lee G. Mundy, Q. Nguyễn Lương, Nicolás Reyes, S. D. Reyes, J.-F. Robitaille, Erik Rosolowsky, N. A. Sandoval-Garrido, F. Schuller, Brian Svoboda, K. Tatematsu, B. Thomasson, D. Walker, Benjamin Wu, A. P. Whitworth, F. Wyrowski

Bibliographic record

VenueAstronomy and Astrophysics · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsUniversity of AlbertaHerzberg Institute of Astrophysics
FundersS. N. Bose National Centre for Basic SciencesInstitut National de Physique Nucléaire et de Physique des ParticulesNational Institutes of Natural SciencesJapan Society for the Promotion of ScienceMinisterio de Ciencia, Innovación y UniversidadesUniversité de BordeauxCentre National de la Recherche ScientifiqueScience and Technology Facilities CouncilNational Astronomical Observatory of JapanEuropean CommissionAgencia Nacional de Investigación y DesarrolloAgence Nationale de la RechercheAgencia Estatal de InvestigaciónNational Radio Astronomy ObservatoryKorea Astronomy and Space Science InstituteNational Science Foundation
KeywordsPhysicsAstrophysicsStarsMolecular cloudStar formationInitial mass functionMilky WayAstronomy

Abstract

fetched live from OpenAlex

Aims. Thanks to the high angular resolution, sensitivity, image fidelity, and frequency coverage of ALMA, we aim to improve our understanding of star formation. One of the breakthroughs expected from ALMA, which is the basis of our Cycle 5 ALMA-IMF Large Program, is the question of the origin of the initial mass function (IMF) of stars. Here we present the ALMA-IMF protocluster selection, first results, and scientific prospects. Methods. ALMA-IMF imaged a total noncontiguous area of ~53 pc 2 , covering extreme, nearby protoclusters of the Milky Way. We observed 15 massive (2.5 −33 × 10 3 M ⊙ ), nearby (2−5.5 kpc) protoclusters that were selected to span relevant early protocluster evolutionary stages. Our 1.3 and 3 mm observations provide continuum images that are homogeneously sensitive to point-like cores with masses of ~0.2 M ⊙ and ~0.6 M ⊙ , respectively, with a matched spatial resolution of ~2000 au across the sample at both wavelengths. Moreover, with the broad spectral coverage provided by ALMA, we detect lines that probe the ionized and molecular gas, as well as complex molecules. Taken together, these data probe the protocluster structure, kinematics, chemistry, and feedback over scales from clouds to filaments to cores. Results. We classify ALMA-IMF protoclusters as Young (six protoclusters), Intermediate (five protoclusters), or Evolved (four proto-clusters) based on the amount of dense gas in the cloud that has potentially been impacted by H II region(s). The ALMA-IMF catalog contains ~700 cores that span a mass range of ~0.15 M ⊙ to ~250 M ⊙ at a typical size of ~2100 au. We show that this core sample has no significant distance bias and can be used to build core mass functions (CMFs) at similar physical scales. Significant gas motions, which we highlight here in the G353.41 region, are traced down to core scales and can be used to look for inflowing gas streamers and to quantify the impact of the possible associated core mass growth on the shape of the CMF with time. Our first analysis does not reveal any significant evolution of the matter concentration from clouds to cores (i.e., from 1 pc to 0.01 pc scales) or from the youngest to more evolved protoclusters, indicating that cloud dynamical evolution and stellar feedback have for the moment only had a slight effect on the structure of high-density gas in our sample. Furthermore, the first-look analysis of the line richness toward bright cores indicates that the survey encompasses several tens of hot cores, of which we highlight the most massive in the G351.77 cloud. Their homogeneous characterization can be used to constrain the emerging molecular complexity in protostars of high to intermediate masses. Conclusions. The ALMA-IMF Large Program is uniquely designed to transform our understanding of the IMF origin, taking the effects of cloud characteristics and evolution into account. It will provide the community with an unprecedented database with a high legacy value for protocluster clouds, filaments, cores, hot cores, outflows, inflows, and stellar clusters studies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.909
Threshold uncertainty score0.857

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.213
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations95
Published2021
Admission routes1
Has abstractyes

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