The (black hole mass)-(color) relations for early- and late-type galaxies: red and blue sequences

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Dullo, Bililign T.
Bouquin, Alexandre Y. K.
Gil de Paz, Armando
Knapen, Johan H.
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IoP Publishing Ltd
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Tight correlations between supermassive black hole (SMBH) mass (M_(BH)) and the properties of the host galaxy have useful implications for our understanding of the growth of SMBHs and evolution of galaxies. Here, we present newly observed correlations between M_(BH) and the host galaxy total UV− [3.6] color (C_(UV,tot), Pearson’s r = 0.6 − 0.7) for a sample of 67 galaxies (20 early-type galaxies and 47 late-type galaxies) with directly measured MBH in the GALEX /S^(4)G survey. The colors are carefully measured in a homogeneous manner using the galaxies’ FUV, NUV and 3.6 µm magnitudes and their multi-component structural decompositions in the literature. We find that more massive SMBHs are hosted by (early- and late-type) galaxies with redder colors, but the M_(BH)−C_(UV,tot) relations for the two morphological types have slopes that differ at ∼ 2σ level. Early-type galaxies define a red sequence in the M_(BH) – C_(UV,tot) diagrams, while late-type galaxies trace a blue sequence. Within the assumption that the specific star formation rate of a galaxy (sSFR) is well traced by L_(UV)/L_(3.6), it follows that the SMBH masses for late-type galaxies exhibit a steeper dependence on sSFR than those for early-type galaxies. The M_(BH) – C_(UV,tot) and M_(BH) – L_(3.6,tot) relations for the sample galaxies reveal a comparable level of vertical scatter in the log MBH direction, roughly 5% − 27% more than the vertical scatter of the M_(BH) −σ relation. Our M_(BH) – C_(UV,tot) relations suggest different channels of SMBH growth for early- and late-type galaxies, consistent with their distinct formation and evolution scenarios. These new relations offer the prospect of estimating SMBH masses reliably using only the galaxy color. Furthermore, we show that they are capable of estimating intermediate black hole masses in low-mass, early- and late-type galaxies.
© 2020. The American Astronomical Society. We thank the referee for their useful comments. B.T.D acknowledges support from a Spanish postdoctoral fellowship ‘Ayudas 1265 para la atracción del talento investigador. Modalidad 2: jóvenes investigadores.’ funded by Comunidad de Madrid under grant number 2016-T2/TIC-2039. B.T.D acknowledges support from grant ‘Ayudas para la realización de proyectos de I+D para jóvenes doctores 2019.’ funded by Comunidad de Madrid and Universidad Complutense de Madrid under grant number PR65/19-22417. We acknowledge financial support from the Spanish Ministry of Economy and Competitiveness (MINECO) under grant numbers AYA2016-75808-R and RTI, which is partly funded by the European Regional Development Fund, and from the Excellence Network MaegNet (AYA2017- 90589-REDT). A.Y.K.B. acknowledges financial support from the Spanish Ministry of Economy and Competitiveness (MINECO), project Estallidos AYA2016-79724- C4-2-P. J.H.K. acknowledges financial support from the European Union’s Horizon 2020 research and innovation programme under Marie Sklodowska-Curie grant agreement No 721463 to the SUNDIAL ITN network, from the State Research Agency (AEI) of the Spanish Ministry of Science, Innovation and Universities (MCIU) and the European Regional Development Fund (FEDER) under the grant with reference AYA2016-76219-P, from IAC project P/300724, financed by the Ministry of Science, Innovation and Universities, through the State Budget and by the Canary Islands Department of Economy, Knowledge and Employment, through the Regional Budget of the Autonomous Community, and from the Fundación BBVA under its 2017 programme of assistance to scientific research groups, for the project “Using machinelearning techniques to drag galaxies from the noise in deep imaging”. J.G. acknowledges financial support from the Spanish Ministry of Economy and Competitiveness under grant number AYA2016-77237-C3-2P.
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