|
|
|
Measuring stellar populations, dust attenuation and ionized gas at kpc scales in 10010 nearby galaxies using the integral field spectroscopy from MaNGA |
| Niu Li(李牛)† and Cheng Li(李成)‡ |
| Department of Astronomy, Tsinghua University, Beijing 100084, China |
|
|
|
|
Abstract As one of the three major experiments of the fourth-generation Sloan Digital Sky Survey (SDSS-IV), the Mapping Nearby Galaxies at Apatch Point Observatory (MaNGA) survey has obtained high-quality integral field spectroscopy (IFS) with a resolution of 1-2 kpc for ～104 galaxies in the local universe during its six-year operation from July 2014 through August 2020. It is crucial to reliably measure the physical properties of the different components in each spectrum before one can use the data for any scientific study. In the past years we have made lots of efforts to develop a novel technique of full spectral fitting, which estimates a model-independent dust attenuation curve from each spectrum, thus allowing us to break the degeneracy between dust attenuation and stellar population properties when fitting the spectrum with stellar population synthesis models. We have applied our technique to the final data release of MaNGA, and obtained measurements of stellar population properties and emission line parameters, as well as the kinematics and dust attenuation of both stellar and ionized gas components. In this paper we describe our technique and the content and format of our data products. The whole dataset is publicly available in Science Data Bank with the link https://doi.org/10.57760/sciencedb.j00113.00088.
|
Received: 19 November 2022
Revised: 03 January 2023
Accepted manuscript online: 06 January 2023
|
|
PACS:
|
98.10.+z
|
(Stellar dynamics and kinematics)
|
| |
98.35.Ln
|
(Stellar content and populations; morphology and overall structure)
|
| |
98.38.Hv
|
(H II regions; emission and reflection nebulae)
|
| |
98.38.Cp
|
(Interstellar dust grains; diffuse emission; infrared cirrus)
|
|
| Fund: This work is supported by the National Key R&D Program of China (Grant No. 2018YFA0404502), and the National Natural Science Foundation of China (Grant Nos. 11821303, 11733002, 11973030, 11673015, 11733004, 11761131004, and 11761141012). |
Corresponding Authors:
Niu Li, Cheng Li
E-mail: liniu@mail.tsinghua.edu.cn;cli2015@tsinghua.edu.cn
|
Cite this article:
Niu Li(李牛) and Cheng Li(李成) Measuring stellar populations, dust attenuation and ionized gas at kpc scales in 10010 nearby galaxies using the integral field spectroscopy from MaNGA 2023 Chin. Phys. B 32 039801
|
[1] Bacon R, Copin Y, Monnet G, et al. 2001 MNRAS 326 23
[2] Bershady Matthew A, Verheijen Marc A W, Swaters Rob A, et al. 2010 ApJ 716 198
[3] Cappellari M, Emsellem E, Krajnović D, et al. 2011 MNRAS 416 1680
[4] Croom Scott M, Lawrence Jon S, Bland-Hawthorn J, et al. 2012 MNRAS 421 872
[5] Sánchez S F, Kennicutt R C, Gil de Paz A, et al. 2012 A&A 538 8
[6] Bundy K, Bershady M A, Law D R, et al. 2015 ApJ 798 7
[7] Poggianti Bianca M, Moretti Alessia, Gullieuszik Marco, et al. 2017 ApJ 844 48
[8] Emsellem E, Schinnerer E, Santoro F, et al. 2022 A&A 659 191
[9] Law D R, Cherinka B, Yan R, et al. 2016 AJ 152 83
[10] Abdurro'uf, Accetta K, Aerts C, et al. 2022 ApJS 259 35
[11] Westfall Kyle B, Cappellari M, Bershady Matthew A, et al. 2019 AJ 158 231
[12] Cappellari M and Emsellem E 2004 PASP 116 138
[13] Cid Fernandes R, Mateus A, Sodré L, et al. 2005 MNRAS 358 363
[14] Sánchez S F, Pérez E, Sánchez-Blázquez P, et al. 2016 RMxAA 52 21
[15] Wilkinson D M, Maraston C, Thomas D, et al. 2015 MNRAS 449 328
[16] Wilkinson D M, Maraston C, Goddard D, et al. 2017 MNRAS 472 4297
[17] Li N, Li C, Mo H J, et al. 2020 ApJ 896 38
[18] Zhou S, Mo H J, Li C, et al. 2019 MNRAS 485 5256
[19] Liang F H, Li C, Li N, et al. 2020 ApJ 896 121
[20] Liang F H, Li C, Li N, et al. 2021 ApJ 923 120
[21] Zhou S, Mo H J, Li C, et al. 2020 MNRAS 497 4753
[22] Zhou S, Mo H J, Li C, et al. 2021 ApJ 916 38
[23] Li N, Li C, Mo H J, et al. 2021 ApJ 917 72
[24] Chabrier G 2003 PASP 115 763
[25] Blanton M R, Bershady M A, Abolfathi B, et al. 2017 AJ 154 28
[26] Drory N, MacDonald N, Bershady M A, et al. 2015 AJ 149 77
[27] Law David R, Yan R, Bershady Matthew A, et al. 2015 AJ 150 19
[28] Gunn James E, Siegmund Walter A, Mannery Edward J, et al. 2006 AJ 131 2332
[29] Smee Stephen A, Gunn James E, Uomoto A, et al. 2013 AJ 146 32
[30] Blanton Michael R, Kazin E, Muna D, et al. 2011 AJ 142 31
[31] Wake D A, Bundy K, Diamond-Stanic A M, et al. 2017 AJ 154 86
[32] Yan R, Tremonti C, Bershady M A, et al. 2016 AJ 151 8
[33] Yan R, Bundy K, Law D R, et al. 2016 AJ 152 197
[34] Bruzual G and Charlot S 2003 MNRAS 344 1000
[35] Maraston C 2005 MNRAS 362 799
[36] Vazdekis A, Sánchez-Blázquez P, Falcón-Barroso J, et al. 2010 MNRAS 404 1639
[37] Bertelli G, Bressan A, Chiosi C, et al. 1994 A&A 106 275
[38] Li C, Wang T G, Zhou H Y, et al. 2005 AJ 129 669
[39] Deeming T J 1964 MNRAS 127 493
[40] Calzetti D, Armus L, Bohlin R C, et al. 2000 ApJ 533 682
[41] Balogh Michael L, Morris Simon L, Yee H K C, et al. 1999 ApJ 527 54 |
| No Suggested Reading articles found! |
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
Altmetric
|
|
blogs
Facebook pages
Wikipedia page
Google+ users
|
Online attention
Altmetric calculates a score based on the online attention an article receives. Each coloured thread in the circle represents a different type of online attention. The number in the centre is the Altmetric score. Social media and mainstream news media are the main sources that calculate the score. Reference managers such as Mendeley are also tracked but do not contribute to the score. Older articles often score higher because they have had more time to get noticed. To account for this, Altmetric has included the context data for other articles of a similar age.
View more on Altmetrics
|
|
|
