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arXiv · 1911.00090

SDSS-IV MaNGA: Bar pattern speed estimates with the Tremaine-Weinberg method and their error sources

L. Garma-Oehmichen·M. Cano-Díaz·H. Hernández-Toledo·E. Aquino-Ortíz·O. Valenzuela·J. A. L. Aguerri·S. F. Sánchez·M. Merrifield
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Abstract

Estimating the bar pattern speed (\Om{}) is one of the main challenges faced in understanding the role of stellar bars in galaxy dynamical evolution. This work aims to characterise different uncertainty sources affecting the Tremaine Weinberg (TW)-method to study the correlation between bar and galaxies physical parameters. We use a sample of 15 MaNGA SDSS-IV galaxies and 3 CALIFA galaxies from \cite{Aguerri2015}. We studied the errors related with (i) galaxy centre determination, (ii) disc position angle (PA) emphasising the difficulties triggered by outer non-axisymmetric structures besides the bar, (iii) the slits length and (iv) the spatial resolution. In average, the PA uncertainties range $\sim 15 \%$, the slit length $\sim 9 \%$ and the centring error $\sim 5 \%$. Reducing the spatial resolution increases the sensitivity to the PA error. Through Monte Carlo simulations, we estimate the probability distribution of the \R{} bar speed parameter. The present sample is composed of 7 slow, 4 fast and 7 ultrafast bars, with no trend with morphological types. Although uncertainties and low sample numbers may mask potential correlations between physical properties, we present a discussion of them: We observe an anti-correlation of \Om{} with the bar length and the stellar mass, suggesting that massive galaxies tend to host longer and slower bars. We also observe a correlation of the molecular gas fraction with \R{}, and a weak anti-correlation with \Om{}, suggesting that bars rotate slower in gaseous discs. Confirmation of such trends awaits future studies.

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L. Garma-Oehmichen, M. Cano-Díaz, H. Hernández-Toledo, E. Aquino-Ortíz, O. Valenzuela, J. A. L. Aguerri, S. F. Sánchez, M. Merrifield. 2019-10-31. SDSS-IV MaNGA: Bar pattern speed estimates with the Tremaine-Weinberg method and their error sources. https://doi.org/10.1093/mnras%2Fstz3101

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