What drives bar rotation? The effect of internal properties and galaxy interactions on bar pattern speeds

TL;DR

The paper investigates what drives bar rotation by analyzing bar pattern speeds and the rotation rate $\mathscr{R}=R_{\mathrm{corot}}/R_{\mathrm{bar}}$ in 27 high-temporal-resolution Auriga simulations. It finds that bars typically lengthen with relatively constant corotation, causing $\mathscr{R}$ to decrease over time and bars to become faster; the strongest predictor of fast bars is inner baryon dominance, with higher $V_*/V_{\mathrm{tot}}$ in the inner regions correlating with smaller $\mathscr{R}$. While stellar mass and abundance-matching offsets also influence bar speeds, external interactions play a secondary role, contributing modestly to changes in rotation rate. The results support a picture in which baryonic content counters dynamical friction and enables rapid bar evolution in Milky Way–mass discs, aligning with several observational trends and offering concrete tests for $\Lambda$CDM–based galaxy formation physics.

Abstract

One of the main properties of galactic bars is their rotation (or pattern) speed, which is driven by both internal galactic properties, as well as external interactions. To assess the influence of these internal and external drivers on bar rotation in a cosmological setting, we use the Auriga suite of cosmological hydrodynamical zoom-in simulations. We calculate the bar pattern speed and the bar rotation rate - the ratio of corotation radius to bar length - at the time of bar formation and at z=0, and compare these to bar age, bar strength, baryon dominance, galaxy stellar mass, and the history of external galaxy interactions. We find that galaxies which are more baryon dominated at z=0 - and which lie above the observed stellar mass-halo mass abundance matching relation - host faster bars, while more dark matter dominated galaxies host slower bars. Baryon-dominated galaxies also form their bars earlier and their rotation rates stay constant or even decrease over time; this leads to older bars being faster than their younger counterparts - in contrast to the expectation of bar slow-down from dynamical friction imparted by the dark matter halo. We also find a trend in stellar mass, with 'faster' bars being hosted in more massive galaxies, which could be driven by the underlying higher baryon-dominance of more massive galaxies. Furthermore, we find that external interactions, such as mergers and flybys, correlate with lower bar rotation rates, particularly for strong interactions that occur around bar formation time. This correlation is relatively weak, leaving internal baryon-dominance as the main driver of fast bar rotation rates.

Figures (12)

• Figure 1: Summary of the main bar parameters used for halo 22 of the Auriga simulations plotted against lookback time. The top panel shows the pattern speed of the bar, from the bar formation time onwards. The second panel shows the bar length calculated from the $A_2$ Fourier mode (orange) and the corotation radius (blue) from the bar formation time onwards, alongside the disc extent (black). The colour scale shows the radial profile of the $A_2$ Fourier mode with lighter, yellower colours indicating higher values. The white crosses give the values of bar length from ellipse fitting. The third panel shows the maximum of the $A_2$ Fourier mode at each time, which we also define as our bar strength; the red dashed line indicates $A_{2\mathrm{,max}}=0.2$, our cut-off for bar formation. The bottom panel shows the rotation rate as calculated from the bar length with $A_2$ and corotation rate (blue line), with the red dashed lines indicating rotation rates of $1$ and $1.4$. The white crosses give the values of rotation rate using bar lengths from ellipse fitting, as used in our results. In all panels, the vertical solid black line shows the time of bar formation $t_\mathrm{bar}$, and the vertical black dashed line shows $0.5\,\mathrm{Gyr}$ later, when we take our measurements at $t_\mathrm{i}$.
• Figure 2: An illustrative example of the Elmegreen parameter calculation for one interacting halo in Au22. Shown against lookback time, the panels show from top to bottom: the halo mass for the perturber (blue) and main halo (orange); the distance between the main halo and the perturber (blue) and the extent of the disc in the main halo (orange); the time to complete $1\,\mathrm{rad}$ of orbit around the centre of the main halo for the perturber (blue) and stars at the edge of the disc (orange); the resulting Elmegreen parameter (blue line) with its local maxima (black crosses). Other interactions in Au22 are shown by the grey crosses.
• Figure 3: Bar length and corotation radius for each halo in our barred sample, with uncertainties, at $t_\mathrm{i}$ (left panel) and $z=0$ (right panel). The colour scale indicates the bar formation time in each case. In the right panel, we also plot in grey with uncertainties the observational bar lengths and corotation radii from 2011Co (downwards triangles), 2015Ag2002Pa2015GB (upwards triangles), 2019Gu (upwards tri-points), 2022GO (downwards tri-points), and 2023Ge (crosses). The upper and lower dashed red lines correspond to ratios of $1.4$ and $1$ respectively, with the red labels in the left panel indicating the resulting slow, fast, and ultrafast regions.
• Figure 4: Top: the relation between bar formation time and pattern speed at $z=0$, shown as the black points, and at $0.5\,\mathrm{Gyr}$ after bar formation, shown as the connected light grey points. Bottom: the same, but for $\mathscr{R}$ instead of pattern speed. The red dashed lines indicate $\mathscr{R}=1,1.4$.
• Figure 5: The dependence at $z=0$ of bar pattern speed and rotation rate on bar strength. The top panel shows the pattern speed at $z=0$$\Omega_{\mathrm{p,}0}$, coloured by the rotation rate at $z=0$$\mathscr{R}_0$, while the bottom panel shows $\mathscr{R}_0$ on the axis and $\Omega_{\mathrm{p,}0}$ in the colour scale. Both have error bars shown. The bottom panel shows red dashed lines indicating $\mathscr{R}=1,1.4$.