The Nearby Evolved Stars Survey III: First data release of JCMT CO-line observations
S. H. J. Wallström et al., and the NESS Collaboration
| Autores: | , , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/416306 |
| Acceso en línea: | http://hdl.handle.net/10261/416306 http://arxiv.org/abs/2510.14809v1 |
| Access Level: | acceso abierto |
| Palabra clave: | Circumstellar matter Stars: AGB and post-AGB Stars: carbon Stars: evolution Stars: low-mass |
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The Nearby Evolved Stars Survey III: First data release of JCMT CO-line observations |
| title |
The Nearby Evolved Stars Survey III: First data release of JCMT CO-line observations |
| spellingShingle |
The Nearby Evolved Stars Survey III: First data release of JCMT CO-line observations Wallström, S. H.J. Circumstellar matter Stars: AGB and post-AGB Stars: carbon Stars: evolution Stars: low-mass |
| title_short |
The Nearby Evolved Stars Survey III: First data release of JCMT CO-line observations |
| title_full |
The Nearby Evolved Stars Survey III: First data release of JCMT CO-line observations |
| title_fullStr |
The Nearby Evolved Stars Survey III: First data release of JCMT CO-line observations |
| title_full_unstemmed |
The Nearby Evolved Stars Survey III: First data release of JCMT CO-line observations |
| title_sort |
The Nearby Evolved Stars Survey III: First data release of JCMT CO-line observations |
| dc.creator.none.fl_str_mv |
Wallström, S. H.J. Kemper, Francisca NESS Collaboration |
| author |
Wallström, S. H.J. |
| author_facet |
Wallström, S. H.J. Kemper, Francisca NESS Collaboration |
| author_role |
author |
| author2 |
Kemper, Francisca NESS Collaboration |
| author2_role |
author author |
| dc.contributor.none.fl_str_mv |
European Research Council Ministerio de Ciencia, Innovación y Universidades (España) Agencia Estatal de Investigación (España) Ministerio de Ciencia e Innovación (España) European Commission Wallström, S. H.J. [0000-0001-8345-7097] Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72] |
| dc.subject.none.fl_str_mv |
Circumstellar matter Stars: AGB and post-AGB Stars: carbon Stars: evolution Stars: low-mass |
| topic |
Circumstellar matter Stars: AGB and post-AGB Stars: carbon Stars: evolution Stars: low-mass |
| description |
S. H. J. Wallström et al., and the NESS Collaboration |
| publishDate |
2025 |
| dc.date.none.fl_str_mv |
2025 2026 2026 |
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info:eu-repo/semantics/article http://purl.org/coar/resource_type/c_6501 Publisher's version info:eu-repo/semantics/publishedVersion |
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article |
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publishedVersion |
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http://hdl.handle.net/10261/416306 http://arxiv.org/abs/2510.14809v1 |
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http://hdl.handle.net/10261/416306 http://arxiv.org/abs/2510.14809v1 |
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Inglés |
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Inglés |
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info:eu-repo/semantics/openAccess |
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openAccess |
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EDP Sciences |
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EDP Sciences |
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reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC instname:Consejo Superior de Investigaciones Científicas (CSIC) |
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The Nearby Evolved Stars Survey III: First data release of JCMT CO-line observationsWallström, S. H.J.Kemper, FranciscaNESS CollaborationCircumstellar matterStars: AGB and post-AGBStars: carbonStars: evolutionStars: low-massS. H. J. Wallström et al., and the NESS CollaborationLow- to intermediate-mass ($\sim$0.8$-$8 M$_\odot$) evolved stars contribute significantly to the chemical enrichment of the interstellar medium in the local Universe, making accurate mass-return estimates in their final stages crucial. The Nearby Evolved Stars Survey (NESS) is a large multi-telescope project targeting a volume-limited sample of $\sim$850 stars within 3 kpc in order to derive the dust and gas return rates in the Solar Neighbourhood, and to constrain the physics underlying these processes. We present an initial analysis of the CO-line observations, including detection statistics, carbon isotopic ratios, initial mass-loss rates, and gas-to-dust ratios. We describe a new data reduction pipeline to analyse the available NESS CO data from the JCMT, measuring line parameters and calculating empirical gas mass-loss rates. We present the first release of the available data on 485 sources, one of the largest homogeneous samples of CO data to date. Comparison with a large literature sample finds that high mass-loss rate and especially carbon-rich sources are over-represented in literature, while NESS is probing significantly more sources at low mass-loss rates, detecting 59 sources in CO for the first time and providing useful upper limits. CO line detection rates are 81% for the CO (2--1) line and 75% for CO (3--2). The majority (82%) of detected lines conform to the expected soft parabola shape, while eleven sources show a double wind. Calculated mass-loss rates show power-law relations with both the dust-production rates and expansion velocities up to $\sim 5 \times 10^{-6}$~\msunyr. Median gas-to-dust ratios of 250 and 680 are found for oxygen-rich and carbon-rich sources, respectively. Our analysis of CO observations in this first data release highlights the importance of our volume-limited approach in characterizing the local AGB population as a whole.S.H.J.W. acknowledges support from the Research Foundation Flanders (FWO) through grant 1285221N, from the ERC consolidator grant 646758 AEROSOL, from the Ministry of Science and Technology of Taiwan under grants MOST104-2628-M-001-004-MY3 and MOST107-2119-M-001-031-MY3, and from Academia Sinica under AS-IA-106-M03. SS acknowledges support from UNAM-PAPIIT Programs IA104822 and IA104824. F.K. acknowledges support from the Spanish Ministry of Science, Innovation and Universities, under grant number PID2023-149918NB-I00. This work was also partly supported by the Spanish program Unidad de Excelencia María de Maeztu CEX2020-001058-M, financed by MCIN/AEI/10.13039/501100011033. T.D. is supported in part by the Australian Research Council through a Discovery Early Career Researcher Award (DE230100183). M.M. and R.W. acknowledge support from the STFC Consolidated grant (ST/W000830/1). J.H. thanks the support of NSFC project 11873086. H.K. thanks the support of the National Research Foundation of Korea (NRF) grant (RS-2021-NR058398) and the Korea Astronomy and Space Science Institute (KASI) grant (Project No. 2025184102), both funded by the Korean Government (MSIT). J.P.M. acknowledges research support by the National Science and Technology Council of Taiwan under grant NSTC 112-2112-M-001-032-MY3. The James Clerk Maxwell Telescope is operated by the East Asian Observatory on behalf of The National Astronomical Observatory of Japan; Academia Sinica Institute of Astronomy and Astrophysics; the Korea Astronomy and Space Science Institute; Center for Astronomical Mega-Science (as well as the National Key R&D Program of China with No. 2017YFA0402700). Additional funding support is provided by the Science and Technology Facilities Council of the United Kingdom and participating universities in the United Kingdom and Canada. This paper made use of JCMT observations under program IDs M17BL002 and M20AL014. The James Clerk Maxwell Telescope has historically been operated by the Joint Astronomy Centre on behalf of the Science and Technology Facilities Council of the United Kingdom, the National Research Council of Canada and the Netherlands Organisation for Scientific Research. The Starlink software (Currie et al. 2014) is currently supported by the East Asian Observatory. This research used the Canadian Advanced Network For Astronomy Research (CANFAR) operated in partnership by the Canadian Astronomy Data Centre and The Digital Research Alliance of Canada with support from the National Research Council of Canada the Canadian Space Agency, CANARIE and the Canadian Foundation for Innovation. This work is sponsored (in part) by the Chinese Academy of Sciences (CAS), through a grant to the CAS South America Center for Astronomy (CASSACA) in Santiago, Chile. This work has made use of Python packages Pyspeckit (Ginsburg et al. 2022), PyVO (Graham et al. 2014), Astropy (Robitaille et al. 2013; Price-Whelan et al. 2018, 2022), SciPy (Virtanen et al. 2020), pandas (McKinney 2010), NumPy (Harris et al. 2020), and Matplotlib (Hunter 2007). This research has made use of the SIMBAD (Wenger et al. 2000) database, operated at CDS, Strasbourg, France. This research has made use of NASA’s Astrophysics Data System Bibliographic ServicesWith funding from the Spanish government through the "María de Maeztu Unit of Excellence" accreditation (CEX2020-001058-M)Peer reviewedEDP SciencesEuropean Research CouncilMinisterio de Ciencia, Innovación y Universidades (España)Agencia Estatal de Investigación (España)Ministerio de Ciencia e Innovación (España)European CommissionWallström, S. H.J. [0000-0001-8345-7097]Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202620262025info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10261/416306http://arxiv.org/abs/2510.14809v1reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/EC/H2020/646758info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2023-149918NB-I00info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/CEX2020-001058-MThe underlying dataset has been published as supplementary material of the article in the publisher platform at DOI 10.1051/0004-6361/202556298https://doi.org/10.1051/0004-6361/202556298Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/4163062026-05-22T06:33:51Z |
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15.812429 |