Unifying static analysis of gravitational structures with a scale-dependent scalar field gravity as an alternative to dark matter

Aims. We investigated the gravitational effects of a scalar field within scalar-tensor gravity as an alternative to dark matter. Motivated by chameleon, symmetron and f(R)-gravity models, we studied a phenomenological scenario where the scalar field has both a mass (i.e. interaction length) and a coupling constant to the ordinary matter which scale with the local properties of the considered astrophysical system. Methods. We analysed the feasibility of this scenario using the modified gravitational potential obtained in its context and applied it to the galactic and hot gas/stellar dynamics in galaxy clusters and elliptical/spiral galaxies respectively. This is intended to be a first step in assessing the viability of this new approach in the context of "alternative gravity" models. Results. The main results are: 1. the velocity dispersion of elliptical galaxies can be fitted remarkably well by the suggested scalar field, with model significance similar to a classical Navarro-Frenk-White dark halo profile; 2. the analysis of the stellar dynamics and the gas equilibrium in elliptical galaxies has shown that the scalar field can couple with ordinary matter with different strengths (different coupling constants) producing and/or depending on the different clustering state of matter components; 3. elliptical and spiral galaxies, combined with clusters of galaxies, show evident correlations among theory parameters which suggest the general validity of our results at all scales and a way toward a possible unification of the theory for all types of gravitational systems we considered. All these results demonstrate that the proposed scalar field scenario can work fairly well as an alternative to dark matter.Comment: 23 pages, 15 figures, 5 tables, accepted for publication on Astronomy & Astrophysic

The central dark matter content of early-type galaxies: scaling relations and connections with star formation histories

We examine correlations between masses, sizes and star formation histories for a large sample of low-redshift early-type galaxies, using a simple suite of dynamical and stellar population models. We confirm an anticorrelation between the size and stellar age and go on to survey for trends with the central content of dark matter (DM). An average relation between the central DM density and galaxy size of 〈ρDM〉∝R−2eff provides the first clear indication of cuspy DM haloes in these galaxies - akin to standard Λ cold dark matter haloes that have undergone adiabatic contraction. The DM density scales with galaxy mass as expected, deviating from suggestions of a universal halo profile for dwarf and late-type galaxies. We introduce a new fundamental constraint on galaxy formation by finding that the central DM fraction decreases with stellar age. This result is only partially explained by the size-age dependencies, and the residual trend is in the opposite direction to basic DM halo expectations. Therefore, we suggest that there may be a connection between age and halo contraction and that galaxies forming earlier had stronger baryonic feedback, which expanded their haloes, or lumpier baryonic accretion, which avoided halo contraction. An alternative explanation is a lighter initial mass function for older stellar population

VEGAS: A VST Early-type GAlaxy Survey. III. Mapping the galaxy structure, interactions and intragroup light in the NGC 5018 group

Most of the galaxies in the Universe at present day are in groups, which are key to understanding the galaxy evolution. In this work we present a new deep mosaic of 1.2 x 1.0 square degrees of the group of galaxies centered on NGC 5018, acquired at the ESO VLT Survey Telescope. We use u, g, r images to analyse the structure of the group members and to estimate the intra-group light. Taking advantage of the deep and multiband photometry and of the large field of view of the VST telescope, we studied the structure of the galaxy members and the faint features into the intra-group space and we give an estimate of the intragroup diffuse light in the NGC 5018 group of galaxies. We found that ~ 41% of the total g-band luminosity of the group is in the form of intragroup light (IGL). The IGL has a (g - r) color consistent with those of other galaxies in the group, indicating that the stripping leading to the formation of IGL is ongoing. From the study of this group we can infer that there are at least two different interactions involving the group members: one between NGC 5018 and NGC 5022, which generates the tails and ring-like structures detected in the light, and another between NGC 5022 and MCG-03-34-013 that have produced the HI tail. A minor merging event also happened in the formation history of NGC 5018 that have perturbed the inner structure of this galaxy.Comment: 21 pages, 15 figures. Accepted for publication in Ap

Statistical analysis of probability density functions for photometric redshifts through the KiDS-ESO-DR3 galaxies

Despite the high accuracy of photometric redshifts (zphot) derived using Machine Learning (ML) methods, the quantification of errors through reliable and accurate Probability Density Functions (PDFs) is still an open problem. First, because it is difficult to accurately assess the contribution from different sources of errors, namely internal to the method itself and from the photometric features defining the available parameter space. Second, because the problem of defining a robust statistical method, always able to quantify and qualify the PDF estimation validity, is still an open issue. We present a comparison among PDFs obtained using three different methods on the same data set: two ML techniques, METAPHOR (Machine-learning Estimation Tool for Accurate PHOtometric Redshifts) and ANNz2, plus the spectral energy distribution template fitting method, BPZ. The photometric data were extracted from the KiDS (Kilo Degree Survey) ESO Data Release 3, while the spectroscopy was obtained from the GAMA (Galaxy and Mass Assembly) Data Release 2. The statistical evaluation of both individual and stacked PDFs was done through quantitative and qualitative estimators, including a dummy PDF, useful to verify whether different statistical estimators can correctly assess PDF quality. We conclude that, in order to quantify the reliability and accuracy of any zphot PDF method, a combined set of statistical estimators is required.Comment: Accepted for publication by MNRAS, 20 pages, 14 figure

Total and dark mass from observations of galaxy centers with Machine Learning

The galaxy total mass inside the effective radius encode important information on the dark matter and galaxy evolution model. Total "central" masses can be inferred via galaxy dynamics or with gravitational lensing, but these methods have limitations. We propose a novel approach, based on Random Forest, to make predictions on the total and dark matter content of galaxies using simple observables from imaging and spectroscopic surveys. We use catalogs of multi-band photometry, sizes, stellar mass, kinematic "measurements" (features) and dark matter (targets) of simulated galaxies, from Illustris-TNG100 hydrodynamical simulation, to train a Mass Estimate machine Learning Algorithm (Mela). We separate the simulated sample in passive early-type galaxies (ETGs), both "normal" and "dwarf", and active late-type galaxies (LTGs) and show that the mass estimator can accurately predict the galaxy dark masses inside the effective radius in all samples. We finally test the mass estimator against the central mass estimates of a series of low redshift (z$\leq$0.1) datasets, including SPIDER, MaNGA/DynPop and SAMI dwarf galaxies, derived with standard dynamical methods based on Jeans equations. Dynamical masses are reproduced within 0.30 dex ($\sim2\sigma$), with a limited fraction of outliers and almost no bias. This is independent of the sophistication of the kinematical data collected (fiber vs. 3D spectroscopy) and the dynamical analysis adopted (radial vs. axisymmetric Jeans equations, virial theorem). This makes Mela a powerful alternative to predict the mass of galaxies of massive stage-IV surveys' datasets

LEMON:LEns MOdelling with Neural networks - I. Automated modelling of strong gravitational lenses with Bayesian Neural Networks

The unprecedented number of gravitational lenses expected from new-generation facilities such as the ESA Euclid telescope and the Vera Rubin Observatory makes it crucial to rethink our classical approach to lens-modelling. In this paper, we present LEMON (Lens Modelling with Neural networks): a new machine-learning algorithm able to analyse hundreds of thousands of gravitational lenses in a reasonable amount of time. The algorithm is based on a Bayesian Neural Network: a new generation of neural networks able to associate a reliable confidence interval to each predicted parameter. We train the algorithm to predict the three main parameters of the singular isothermal ellipsoid model (the Einstein radius and the two components of the ellipticity) by employing two simulated data sets built to resemble the imaging capabilities of the Hubble Space Telescope and the forthcoming Euclid satellite. In this work, we assess the accuracy of the algorithm and the reliability of the estimated uncertainties by applying the network to several simulated data sets of 104 images each. We obtain accuracies comparable to previous studies present in the current literature and an average modelling time of just ∼0.5 s per lens. Finally, we apply the LEMON algorithm to a pilot data set of real lenses observed with HST during the SLACS program, obtaining unbiased estimates of their SIE parameters. The code is publicly available on GitHub (https://github.com/fab-gentile/LEMON).</p

CASCO: Cosmological and AStrophysical parameters from Cosmological simulations and Observations -- I. Constraining physical processes in local star-forming galaxies

We compare the structural properties and dark matter content of star-forming galaxies taken from the CAMELS cosmological simulations to the observed trends derived from the SPARC sample in the stellar mass range $[10^{9}, 10^{11}]\,\textrm{M}_{\odot}$, to provide constraints on the value of cosmological and astrophysical (SN- and AGN-related) parameters. We consider the size-, internal DM fraction-, internal DM mass- and total-stellar mass relations for all the 1065 simulations from the IllustrisTNG, SIMBA and ASTRID suites of CAMELS, and search for the parameters that minimize the $\chi^{2}$ with respect to the observations. For the IllustrisTNG suite, we find the following constraints for the cosmological parameters: $\Omega_{\textrm{m}} = 0.27_{-0.05}^{+0.01}$, $\sigma_{8} = 0.83_{-0.11}^{+0.08}$ and $S_{8} = 0.78_{-0.09}^{+0.03}$, which are consistent within $1\sigma$ with the results from the nine-year WMAP observations. SN feedback-related astrophysical parameters, which describe the departure of outflow wind energy per unit star formation rate and wind velocity from the reference IllustrisTNG simulations, assume the following values: $A_{\textrm{SN1}} = 0.48_{-0.16}^{+0.25}$ and $A_{\textrm{SN2}} = 1.21_{-0.34}^{+0.03}$, respectively. Therefore, simulations with a lower value of outflow wind energy per unit star formation rate with respect to the reference illustrisTNG simulation better reproduce the observations. Simulations based on SIMBA and ASTRID suites predict central dark matter masses substantially larger than those observed in real galaxies, which can be reconciled with observations only by requiring values of $\Omega_{\textrm{m}}$ inconsistent with cosmological constraints for SIMBA, or simulations characterized by unrealistic galaxy mass distributions for ASTRID.Comment: 24 pages, 10 figures, 9 tables. Accepted by MNRAS for publication; Added a reference to sec. 4.

A Dearth of Dark Matter in Ordinary Elliptical Galaxies

The kinematics of the outer parts of three intermediate-luminosity elliptical galaxies have been studied using the Planetary Nebula Spectrograph. The galaxies' velocity dispersion profiles are found to decline with radius; dynamical modeling of the data indicates the presence of little if any dark matter in these galaxies' halos. This surprising result conflicts with findings in other galaxy types, and poses a challenge to current galaxy formation theories.Comment: Science, 19 Sep 03, in press, 15 pp., 6 figs (4 color), supporting online material integrated as appendix, uses scicite.sty. See high-res version at http://astro.nottingham.ac.uk/~romanow/res.html and Science Express online at http://www.sciencemag.org/cgi/content/abstract/1087441v

Rejection criteria based on outliers in the KiDS photometric redshifts and PDF distributions derived by machine learning

The Probability Density Function (PDF) provides an estimate of the photometric redshift (zphot) prediction error. It is crucial for current and future sky surveys, characterized by strict requirements on the zphot precision, reliability and completeness. The present work stands on the assumption that properly defined rejection criteria, capable of identifying and rejecting potential outliers, can increase the precision of zphot estimates and of their cumulative PDF, without sacrificing much in terms of completeness of the sample. We provide a way to assess rejection through proper cuts on the shape descriptors of a PDF, such as the width and the height of the maximum PDF's peak. In this work we tested these rejection criteria to galaxies with photometry extracted from the Kilo Degree Survey (KiDS) ESO Data Release 4, proving that such approach could lead to significant improvements to the zphot quality: e.g., for the clipped sample showing the best trade-off between precision and completeness, we achieve a reduction in outliers fraction of $\simeq 75\%$ and an improvement of $\simeq 6\%$ for NMAD, with respect to the original data set, preserving the $\simeq 93\%$ of its content.Comment: Preprint version of the manuscript to appear in the Volume "Intelligent Astrophysics" of the series "Emergence, Complexity and Computation", Book eds. I. Zelinka, D. Baron, M. Brescia, Springer Nature Switzerland, ISSN: 2194-728