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The iMaNGA project uses a forward-modelling approach to compare the predictions of cosmological simulations with observations from SDSS-IV/MaNGA. We investigate the dependency of age and metallicity radial gradients on galaxy morphology, stellar mass, stellar surface mass density ($\Sigma_*$), and environment. The key of our analysis is that observational biases affecting the interpretation of MaNGA data are emulated in the theoretical iMaNGA sample. The simulations reproduce the observed global stellar population scaling relations with positive correlations between galaxy mass and age/metallicity quite well and also produce younger stellar populations in late-type in agreement with observations. We do find interesting discrepancies, though, that can inform the physics and further development of the simulations. Ages of spiral galaxies and low-mass ellipticals are overestimated by about 2-4 Gyr. Radial metallicity gradients are steeper in iMaNGA than in MaNGA, a discrepancy most prominent in spiral and lenticular galaxies. Also, the observed steepening of metallicity gradients with increasing galaxy mass is not well matched by the simulations. We find that the theoretical radial profiles of surface mass density $\Sigma_*$ are steeper than in observations except for the most massive galaxies. In both MaNGA and iMaNGA [Z/H] correlates with $\Sigma_*$, however, the simulations systematically predict lower [Z/H] by almost a factor of 2 at any $\Sigma_*$. Most interestingly, for galaxies with stellar mass $\log M_*\leq 10.80 M_\odot$ the MaNGA data reveal a positive correlation between galaxy radius and [Z/H] at fixed $\Sigma_*$, which is not recovered in iMaNGA. Finally, the dependence on environmental density is negligible in both the theoretical iMaNGA and the observed MaNGA data.

Strengthening the synergy between simulations and observations is essential to test galaxy formation and evolution theories. To achieve this goal, in the first paper of this series, we presented a method to generate mock SDSS-IV/MaNGA integral-field spectroscopic galaxy observations from cosmological simulations. In this second paper, we build the iMaNGA catalogue consisting of $\sim$1,000 unique galaxies from the TNG50 cosmological simulations, selected to mimic the SDSS-IV/MaNGA-Primary sample selection. Here we present and discuss the iMaNGA sample and its comparison to the MaNGA Primary catalogue. The iMaNGA sample well recovers the MaNGA-Primary sample in terms of stellar mass vs angular size relation and spatial resolution. The S\'ersic index vs angular size relation, instead, is not reproduced well by the simulations, mostly because of a paucity of high-mass elliptical galaxies in TNG50. We also investigate our ability to recover the galaxy kinematics and stellar population properties with full-spectral fitting. We demonstrate that 'intrinsic' and `recovered' stellar kinematics, stellar ages and metallicities are consistent, with residuals compatible with zero within 1$-{\sigma}$. Also`intrinsic' and `recovered' star formation histories display a great resemblance. We conclude that our mock generation and spectral fitting processes do not distort the `intrinsic' galaxy properties. Therefore, in the third paper of this series, we can meaningfully test the cosmological simulations, comparing the stellar population properties and kinematics of the iMaNGA mock galaxies and the MaNGA observational results., Comment: Published on MNRAS: 03 May 2023 https://doi.org/10.1093/mnras/stad1337

Galaxy formation and evolution simulations are essential tools to probe poorly known astrophysics processes, but particular care is needed to compare simulations with galaxy observations, as observed data need to be modelled as well. We present a method to generate mock galaxies from the hydro-dynamical IllustrisTNG simulations which are suited to compare with integral field spectroscopic observation of galaxies from the SDSS-IV/MaNGA survey. Firstly, we include the same instrumental effects and procedures as adopted in the acquisition and analysis of real data. Furthermore, we generate the galaxy spectra from the simulations using new stellar population models based on the MaNGA stellar library (MaStar). In this way, our mock data cubes have the same spatial sampling, cover the same wavelength range (3600-10300 \r{A}), and share the same spectral resolution ($R\approx1800$) and flux calibration of real MaNGA galaxy spectra. In this first paper, we demonstrate the method over an early-type and a late-type simulated galaxy from TNG50. We analyse the correspondent mock MaNGA-like data cubes with the same full spectral fitting code, \textsc{FIREFLY}, which was used for the observed spectra. We find that the intrinsic and recovered age and metallicity gradients are consistent within 1${\sigma}$, with residuals over all tassels consistent with $0$ at the 68$\%$ confidence level. We also perform the challenging test at comparing intrinsic and recovered star formation histories, finding a close resemblance between input and output. In follow-up papers, we will present a full simulated MaNGA-like catalogue ($\approx10,000$ galaxies) with a comprehensive comparison of TNG50 simulations to MaNGA observational results.

We present the MaNGA FIREFLY Value-Added-Catalogue (VAC) - a catalogue of ~3.7 million spatially resolved stellar population properties across 10,010 nearby galaxies from the final data release of the MaNGA survey. The full spectral fitting code firefly is employed to derive parameters such as stellar ages, metallicities, stellar and remnant masses, star formation histories, star formation rates and dust attenuation. In addition to Voronoi-binned measurements, our VAC also provides global properties, such as central values and radial gradients. Two variants of the VAC are available: presenting the results from fits using the M11-MILES and the novel MaStar stellar population models. MaStar allows to constrain the fit over the whole MaNGA wavelength range, extends the age-metallicity parameter space, and uses empirical spectra from the same instrument as MaNGA. The fits employing MaStar models find on average slightly younger ages, higher mass-weighted metallicities and smaller colour excesses. These differences are reduced when matching wavelength range and converging template grids. We further report that FIREFLY stellar masses are systematically lower by ~0.3 dex than masses from the MaNGA PCA and Pipe3D VACs, but match masses from the NSA best with only ~0.1 dex difference. Finally, we show that FIREFLY stellar ages correlate with spectral index age indicators H$\delta_A$ and $D_n$(4000), though with a clear additional metallicity dependence., Comment: 20 pages, 16 figures (+appendix). Accepted for publication in MNRAS. The accepted version now also includes star formation rates and performance tests. The MaNGA FIREFLY VAC is publicly available at the SDSS webpage https://www.sdss.org/dr17/manga/manga-data/manga-firefly-value-added-catalog and at ICG Portsmouth's website http://www.icg.port.ac.uk/manga-firefly-vac

Galaxy clusters are biased tracers of the underlying matter density field. At very large radii beyond about 10 Mpc/\textit{h}, the shear profile shows evidence of a second-halo term. This is related to the correlated matter distribution around galaxy clusters and proportional to the so-called halo bias. We present an observational analysis of the halo bias-mass relation based on the AMICO galaxy cluster catalog, comprising around 7000 candidates detected in the third release of the KiDS survey. We split the cluster sample into 14 redshift-richness bins and derive the halo bias and the virial mass in each bin by means of a stacked weak lensing analysis. The observed halo bias-mass relation and the theoretical predictions based on the $\Lambda$CDM standard cosmological model show an agreement within $2\sigma$. The mean measurements of bias and mass over the full catalog give $M_{200c} = (4.9 \pm 0.3) \times 10^{13} M_{\odot}/\textit{h}$ and $b_h \sigma_8^2 = 1.2 \pm 0.1$. With the additional prior of a bias-mass relation from numerical simulations, we constrain the normalization of the power spectrum with a fixed matter density $\Omega_m = 0.3$, finding $\sigma_8 = 0.63 \pm 0.10$.

Context. The large-scale mass distribution around dark matter haloes hosting galaxy clusters provides sensitive cosmological information. Aims. In this work, we make use of a large photometric galaxy cluster sample, constructed from the public Third Data Release of the Kilo-Degree Survey, and the corresponding shear signal, to assess cluster masses and test the concordance ${\Lambda}$-cold dark matter (${\Lambda}$CDM) model. In particular, we study the weak gravitational lensing effects on scales beyond the cluster virial radius, where the signal is dominated by correlated and uncorrelated matter density distributions along the line-of-sight. The analysed catalogue consists of 6962 galaxy clusters, in the redshift range $0.1 \leq z \leq 0.6$ and with signal-to-noise ratio larger than 3.5. Methods. We perform a full Bayesian analysis to model the stacked shear profiles of these clusters. The adopted likelihood function considers both the small-scale 1-halo term, used primarily to constrain the cluster structural properties, and the 2-halo term, that can be used to constrain cosmological parameters. Results. We find that the adopted modelling is successful to assess both the cluster masses and the total matter density parameter, ${\Omega}_M$, when fitting shear profiles up to the largest available scales of 35 Mpc/h. Moreover, our results provide a strong observational evidence of the 2-halo signal in the stacked gravitational lensing of galaxy clusters, further demonstrating the reliability of this probe for cosmological studies. The main result of this work is a robust constraint on ${\Omega}_M$, assuming a flat ${\Lambda}$CDM cosmology. We get ${\Omega}_M = 0.29 \pm 0.02$, estimated from the full posterior probability distribution, consistent with the estimates from cosmic microwave background experiments., Comment: Accepted for publication on A&A, replaced to match the final version: minor comments