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Conventional galaxy mass estimation methods suffer from model assumptions and degeneracies. Machine learning (ML), which reduces the reliance on such assumptions, can be used to determine how well present-day observations can yield predictions for the distributions of stellar and dark matter. In this work, we use a general sample of galaxies from the TNG100 simulation to investigate the ability of multibranch convolutional neural network (CNN) based ML methods to predict the central (i.e. within 1−2 effective radii) stellar and total masses, and the stellar mass-to-light ratio (M */ L). These models take galaxy images and spatially resolved mean velocity and velocity dispersion maps as inputs. Such CNN-based models can, in general, break the degeneracy between baryonic and dark matter in the sense that the model can make reliable predictions on the individual contributions of each component. For example, with r -band images and two galaxy kinematic maps as inputs, our model predicting M */ L has a prediction uncertainty of 0.04 dex. Moreover, to investigate which (global) features significantly contribute to the correct predictions of the properties above, we utilize a gradient-boosting machine. We find that galaxy luminosity dominates the prediction of all masses in the central regions, with stellar velocity dispersion coming next. We also investigate the main contributing features when predicting stellar and dark matter mass fractions (f *, f DM) and the dark matter mass M DM, and discuss the underlying astrophysics. [ABSTRACT FROM AUTHOR]

The effect of angular momentum on galaxy formation and evolution has been studied for several decades. Our recent two papers using IllustrisTNG-100 simulation have revealed the acquisition path of the angular momentum from large-scale environment (satellites within hundreds of kpc) through the circumgalactic medium (CGM) to the stellar discs, putting forward the co-rotation scenario across the three distance scales. In real observations, although the rotation signature for the CGM and environmental three-dimensional angular momentum are difficult to obtain, line-of-sight kinematics of group member galaxies and stellar disc kinematics of central galaxies are available utilizing existing group catalogue data and integral field unit (IFU) data. In this paper, we use (1) the group catalogue of SDSS DR7 and MaNGA IFU stellar kinematic maps and (2) the group catalogue of GAMA DR4 data and SAMI IFU stellar kinematic maps, to test if the prediction above can be seen in real data. We found the co-rotation pattern between stellar discs and satellites can be concluded with 99.7 per cent confidence level (∼3σ) when combining the two data sets. And the random tests show that the signal can be scarcely drawn from random distribution. [ABSTRACT FROM AUTHOR]

We present dynamical scaling relations, combined with the stellar population properties, for a subsample of about 6000 nearby galaxies with the most reliable dynamical models extracted from the full Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) sample of 10 000 galaxies. We show that the inclination-corrected mass plane for both early-type galaxies (ETGs) and late-type galaxies (LTGs), which links dynamical mass, projected half-light radius R e, and the second stellar velocity moment σe within R e, satisfies the virial theorem and is even tighter than the uncorrected one. We find a clear parabolic relation between |$\lg (M/L)_{\rm e}$|⁠ , the total mass-to-light ratio (M / L) within a sphere of radius R e, and |$\lg \sigma _{\rm e}$|⁠ , with the M / L increasing with σe and for older stellar populations. However, the relation for ETGs is linear and the one for the youngest galaxies is constant. We confirm and improve the relation between mass-weighted total density slopes |$\overline{\gamma _{_{\rm T}}}$| and σe: |$\overline{\gamma _{_{\rm T}}}$| become steeper with increasing σe until |$\lg (\sigma _{\rm e}/{\rm km\, s^{-1}})\approx 2.2$| and then remain constant around |$\overline{\gamma _{_{\rm T}}}\approx 2.2$|⁠. The |$\overline{\gamma _{_{\rm T}}}\!-\!\sigma _{\rm e}$| variation is larger for LTGs than ETGs. At fixed σe the total density profiles steepen with galaxy age and for ETGs. We find generally low dark matter fractions, median f DM(< R e) = 8 per cent, within a sphere of radius R e. However, we find that f DM(< R e) depends on σe better than stellar mass: dark matter increases to a median f DM(< R e) = 33 per cent for galaxies with |$\sigma _{\rm e}\lesssim 100$|  km s−1. The increased f DM(< R e) at low σe explains the parabolic |$\lg (M/L)_{\rm e}\!-\!\lg \sigma _{\rm e}$| relation. [ABSTRACT FROM AUTHOR]

We present the measurement of total and stellar/dark matter decomposed mass density profile around a sample of galaxy groups and clusters with dynamical masses derived from integral-field stellar kinematics from the MaNGA survey in Paper I and weak lensing derived from the DECaLS imaging survey. Combining the two data sets enables accurate measurement of the radial density distribution from several kpc to Mpc scales. Intriguingly, we find that the excess surface density derived from stellar kinematics in the inner region cannot be explained by simply adding an NFW dark matter halo extrapolated from lensing measurement at a larger scale to a stellar mass component derived from the NASA-Sloan Atlas (NSA) catalogue. We find that a good fit to both data sets requires a stellar mass normalization about three times higher than that derived from the NSA catalogue, which would require an unrealistically too-heavy initial mass function for stellar mass estimation. If we keep the stellar mass normalization to that of the NSA catalogue but allow a varying inner dark matter density profile, we obtain an asymptotic slope of γgnfw =  |$1.82_{-0.25}^{+0.15}$| and γgnfw =  |$1.48_{-0.41}^{+0.20}$| for the group bin and the cluster bin, respectively, significantly steeper than the NFW case. We also compare the total mass inner density slopes with those from TNG300 and find that the values from the simulation are lower than the observation by about 2σ level. [ABSTRACT FROM AUTHOR]