Unifying the dynamical classification of early-type galaxies: kinematic deficits in IllustrisTNG versus observations

TL;DR

The paper analyzes ETG kinematics by comparing IllustrisTNG simulations (TNG50, TNG100) with MaNGA and ATLAS${}^{3D}$ IFS data, revealing a deficiency in kinematic bimodality in simulations. It introduces intrinsic dynamical thresholds based on $λ_{R, m intr}$, $κ_{ m rot}$, and $f_{ m spheroid}$ to classify fast versus slow rotators universally, and demonstrates that scaling relations from TNG enable observational inferences of these quantities. A key finding is that TNG produces too many intermediate-rotator systems with larger spheroid/stellar-halo fractions, leading to weaker rotation signals than observed. The work also proposes a method to estimate stellar halo masses from IFS kinematics, highlighting the importance of improved resolution and subgrid physics for accurately capturing galaxy dynamics. Overall, the study provides a unified framework to compare simulated and observed ETG dynamics and underscores areas for improvement in simulations and data interpretation.

Abstract

We conduct a comparative analysis of galaxy kinematics using IllustrisTNG simulations and integral-field spectroscopy (IFS) observations. We identify 2,342 early-type galaxies (ETGs) from the TNG100 simulation and 236 ETGs from the TNG50 simulation, comparing them with observations from MaNGA and ATLAS$^{3D}$. For these systems, we measure key kinematic parameters: the intrinsic spin parameter $λ_{R,\mathrm{intr}}$ (measured edge-on), the cylindrical rotational energy fraction $κ_{\mathrm{rot}}$, and structural mass ratios including the spheroid mass fraction $f_{\mathrm{spheroid}}$ and stellar halo mass fraction $f_{\mathrm{halo}}$. Our study reveals that standard classifiers--the $λ_{R}(R_e)=0.31\sqrt{\varepsilon}$ relation and $\overline{k_5}$ coefficient (higher-order Fourier term of velocity fields)--fail to align with observed kinematic bimodality. We propose revised thresholds: $λ_{R,\mathrm{intr}} \sim 0.4$, $κ_{\mathrm{rot}} \sim 0.5$, and $f_{\mathrm{spheroid}} \sim 0.6$, which classify galaxies into rotation-dominated (fast rotators) and random motion-dominated (slow rotators). Scaling relations from TNG enable observational estimates of $κ_{\mathrm{rot}}$ and $f_{\mathrm{spheroid}}$. The simulations exhibit a bimodality deficit, characterized by a lack of fast rotators and suppressed $λ_{R,\mathrm{intr}}$, attributed to excess galaxies with intermediate rotation and high spheroid/stellar halo mass. We introduce a novel method to estimate $f_{\mathrm{halo}}$ from IFS kinematics, though uncertainties remain.

Figures (12)

• Figure 1: The $g-r$ color-stellar mass diagram. The upper and lower panels of the figure display observational data (from MaNGA and $\text{ATLAS}^{\rm 3D}$) and simulated data (from TNG50 and TNG100), respectively, encompassing all samples within the mass range of $10^{10}-10^{11.5}M_{\odot}$. Red sequence ETGs are selected above the dashed line.
• Figure 2: Mass-size relation. Top: stellar mass distribution function of the chosen sample of ETGs from observational data and the TNG simulations. Bottom: Circularized effective radii $R_e$, of the selected ETG samples in the TNG100 and TNG50 simulations as a function of stellar mass, and comparison with observations (ATLAS$^{\mathrm{3D}}$ and MaNGA). Both TNG50 (green solid line) and TNG100 (gray solid line) galaxies share comparable stellar masses and sizes with the ATLAS$^{\mathrm{3D}}$(red dashed line) and MaNGA (blue dashed line) galaxies. The lines and the points represent the median values, with colored regions and error bars indicating the range from the 16th to 84th percentile of each distribution. To avoid overlap, we shift the error bars slightly for clarity.
• Figure 3: Velocity maps and models of examples of a fast rotator (left) and a slow rotator (right). It shows raw data at the top, a reconstructed velocity field employing a pure cosine law along ellipses in the middle, and residuals depicting deviations at the bottom. Our visualization emphasizes structural features through isodensity ellipses spaced at regular $R_e$ intervals from $R_e$ to $3R_e$. The major axis orientations - with solid lines representing photometrically-derived morphological axes and dashed lines indicating kinematically-determined axes - are both measured at $R_e$.
• Figure 4: The $\lambda_{R}(R_e)-\varepsilon(3R_e)$ diagram color coded by $\kappa_{\rm rot}(\rm{all})$, $f_{\rm spheroid}(\rm{all})$, $f_{\rm halo}(\rm{all})$, and $f_{\rm{bulge}}(\rm all)$ for TNG50 (upper) and TNG100 (lower). Here, $\kappa_{\rm rot}(\rm all)$, $f_{\rm spheroid}(\rm all)$, $f_{\rm halo}(\rm all)$, and $f_{\rm bulge}(\rm all)$ represent the significance of cylindrical rotation, the spheroidal mass fraction, the stellar halo mass fraction, and the bulge mass fraction, respectively (see Section \ref{['sec_structure_mass_ratio']} and \ref{['sec_krot']}). The magenta curve shows the $\lambda_{R}-\varepsilon$ relation in edge-on view for axisymmetric galaxies derived by 2007MNRAS.379..418C. The black dotted curves illustrate this relation across varying $i$, with steps of $\Delta i = 10^{\circ}$. Additionally, the thin black dashed lines represent the theoretical distribution for different rotations spaced at intervals of $\Delta \lambda_{{R,\rm intr}} = 0.1$. The bold black curve represents our proposed new threshold for distinguishing between SRs and FRs. This threshold is derived from the tensor virial theorem for oblate galaxies with intrinsic parameters $\lambda_{{R,\rm intr}}(R_e) = 0.4$ and $\varepsilon_{\text{intr}} = 0.525$, assuming an anisotropy of $\delta = 0.7\varepsilon_{\text{intr}} = 0.367$. For comparison, the thin solid black line is the standard empirical threshold defined by $\lambda_{R}(R_e) = 0.31 \times \sqrt{\varepsilon}$ proposed in 2011MNRAS.414..888E. We present the proportion of SRs classified by our new threshold alongside the standard old threshold at the upper-left corner. We smooth the color data using the locally weighted regression method LOESS Cleveland010919882013MNRAS.432.1862C with a smoothing factor of $0.1$. The blue horizontal dashed line represents the empirical threshold defined by $\lambda_{R}(R_e) = 0.1$ according to 2007MNRAS.379..401E, the black polygon denotes the empirical threshold set by $\lambda_{R}(R_e) < 0.08 + \varepsilon/4 \,\, {\rm and} \,\, \varepsilon < 0.4$ as per 2016ARAA..54..597C, and the green polygon signifies the empirical threshold given by $\lambda_{R}(R_e) < \lambda_{R\text{start}} + \varepsilon/4 \,\, {\rm and} \,\, \varepsilon < 0.35 + \frac{\lambda_{R\text{start}}}{1.538}$ (with $\lambda_{R\text{start}} = 0.12$ when the IFS data quality is comparable to that of SAMI) based on 2021MNRAS.505.3078V.
• Figure 5: The $\lambda_{\rm R}(R_e)-\varepsilon(R_e)$ diagram of the sample of ATLAS$^{\mathrm{3D}}$(left panel) and MaNGA (right panel). The proportions of SRs and FRs classified using our new threshold, compared to the standard old definition, are provided at the top. The definitions of all the lines are the same as those in Figure \ref{['fig:TNG_intrinsic_dynamical_auto_GMM']}.