arXiv subjects

Luciano Casarini

Publications and source records attributed to Luciano Casarini.

At least 19 recordsLinked to original sources

arXiv2026

Reconciling the Fundamental Plane of Early-Type Galaxies with hydrodynamical simulations: The case of IllustrisTNG100-1

The Fundamental Plane (FP) of Early-Type Galaxies (ETGs) encapsulates a tight correlation among their structural and dynamical properties and provides an important benchmark for galaxy formation models. However, cosmological hydrodynamical simulations have historically struggled to reproduce the observed FP tilt, with discrepancies often attributed to to flawed feedback physics or insufficient resolution. Using the IllustrisTNG100-1 simulation, we show that adopting observationally motivated measurements, including Sérsic-derived photometric parameters and dynamically inferred velocity dispersions designed to minimise softening-length effects, substantially reduces the discrepancy between simulated and observed FPs. We further explore the impact of non-universal, mass-dependent Initial Mass Function (IMF) variations through forward modelling of their effects on galaxy structural and dynamical quantities. In particular, bottom-heavy IMF variations produce FP coefficients fully consistent with observational constraints for both direct and orthogonal fits. Our results suggest that a significant fraction of the long-standing FP tension arises from how galaxy observables are extracted and interpreted in simulations, although residual discrepancies may still reflect limitations in the underlying baryonic physics. These findings highlight the importance of observational realism and IMF variations for interpreting galaxy scaling relations and for improving the predictive power of hydrodynamical simulations of ETG formation.

astro-ph.GA↗

arXiv2025

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$0.1) datasets, including SPIDER, MaNGA/DynPop and SAMI dwarf galaxies, derived with standard dynamical methods based on Jeans equations. Dynamical masses are reproduced within 0.30 dex ($\sim2σ$), 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.

astro-ph.GA↗

arXiv2025

The catalogue of virtual early-type galaxies from IllustrisTNG: validation and real observation consistency

Early-type galaxies (ETGs) are reference systems to understand galaxy formation and evolution processes. The physics of their formation and internal dynamics are codified in well-known scaling relations. In this context, cosmological hydrodynamical simulations play an important role in probing the physical origins of scaling relations by providing a controlled environment to study the formation and evolution of galaxies, linking their internal dynamics to underlying physical processes, and testing the robustness of observational inference methods. In this work, we present the closest-to-reality sample of ETGs from the IllustrisTNG100-1 simulation, dubbed "virtual-ETGs", based on an observational-like algorithm that combines standard projected and three-dimensional galaxy structural parameters. We extract 2D photometric information by projecting the galaxies' light into three planes and modelling them via Sérsic profiles. Aperture velocity dispersions, corrected for softened central dynamics, are calculated along the line-of-sight orthogonal to the photometric projection plane. Central mass density profiles assume a power-law model, while 3D masses remain unmodified from the IllustrisTNG catalogue. The final catalogue includes $10121$ galaxies at redshifts $z \leq 0.1$. By comparing the virtual properties with observations, we find that the virtual-ETG scaling relations (e.g., size-mass, size-central surface brightness, and Faber-Jackson), central density slopes, and scaling relations among total density slopes and galaxy structural parameters are generally consistent with observations. We make the virtual-ETG publicly available for galaxy formation studies and plan to use this sample as a training set for machine learning tools to infer galaxy properties in future imaging and spectroscopic surveys.

astro-ph.GA↗

arXiv2025

Interacting dark sector with quadratic coupling: theoretical and observational viability

Models proposing a non-gravitational interaction between dark energy (DE) and dark matter (CDM) have been extensively studied as alternatives to the standard cosmological model. A common approach to describing the DE-CDM coupling assumes it to be linearly proportional to the dark energy density. In this work, we consider the model with interaction term $Q=3Hγ{ρ_{x}^{2}}/{(ρ_{c}+ρ_{x})}$. We show that for positive values of $γ$ this model predicts a future violation of the Weak Energy Condition (WEC) for the dark matter component, and for a specific range of negative values of $γ$ the CDM energy density can be negative in the past. We perform a parameter selection analysis for this model using data from Type Ia supernovae from the Pantheon sample, $H(z)$ measurements from the Cosmic Chronometers sample, Baryon Acoustic Oscillations from the DESI survey, and Cosmic Microwave Background data from the Planck combined with the Hubble constant $H_0$ prior. Imposing a prior to ensure that the WEC is not violated, our model is consistent with $Λ$CDM in 2$σ$ C.L., yet exhibits a preference for smaller values of $σ_8$, alleviating the $σ_8$ tension between the CMB results from Planck 2018 and the weak gravitational lensing observations from the KiDS-1000 cosmic shear survey.

astro-ph.CO↗

arXiv2023

Measuring the Hubble Constant with cosmic chronometers: a machine learning approach

Local measurements of the Hubble constant ($H_0$) based on Cepheids e Type Ia supernova differ by $\approx 5 σ$ from the estimated value of $H_0$ from Planck CMB observations under $Λ$CDM assumptions. In order to better understand this $H_0$ tension, the comparison of different methods of analysis will be fundamental to interpret the data sets provided by the next generation of surveys. In this paper, we deploy machine learning algorithms to measure the $H_0$ through a regression analysis on synthetic data of the expansion rate assuming different values of redshift and different levels of uncertainty. We compare the performance of different regression algorithms as Extra-Trees, Artificial Neural Network, Gradient Boosting, Support Vector Machines, and we find that the Support Vector Machine exhibits the best performance in terms of bias-variance tradeoff in most cases, showing itself a competitive cross-check to non-supervised regression methods such as Gaussian Processes.

astro-ph.CO↗

arXiv2021

Inferring galaxy dark halo properties from visible matter with Machine Learning

Next-generation surveys will provide photometric and spectroscopic data of millions to billions of galaxies with unprecedented precision. This offers a unique chance to improve our understanding of the galaxy evolution and the unresolved nature of dark matter (DM). At galaxy scales, the density distribution of DM is strongly affected by the astrophysical feedback processes, which are difficult to fully account for in classical techniques to derive mass models. In this work, we explore the capability of supervised learning algorithms to predict the DM content of galaxies from luminous observational-like parameters, using the public catalog of the TNG100 simulation. In particular, we use Photometric, Structural and Kinematic parameters to predict the total DM mass, DM half-mass radius, DM mass inside one and two stellar half-mass radii. We adopt the coefficient of determination, $R^2$, as a reference metric to evaluate the accuracy of these predictions. We find that the Photometric features alone are able to predict the total DM mass with fair accuracy, while Structural and Photometric features together are more effective to determine the DM inside the stellar half mass radius, and the DM within twice the stellar half mass radius. However, using all observational quantities together (Photometry, Structural and Kinematics) incredibly improves the overall accuracy for all DM quantities. This first test shows that Machine Learning tools are promising approaches to derive predictions of the DM in real galaxies. The next steps will be to improve observational realism of the training sets, by closely select samples which accurately reproduce the typical observed luminous scaling relations. The trained pipelines will be suitable for real galaxy data collected from the next-generation surveys like Rubin/LSST, Euclid, CSST, 4MOST, DESI, to derive, e.g., the properties of their central DM fractions.

astro-ph.GA↗

arXiv2021

A model-independent reconstruction of dark sector interactions

Relaxing the conventional assumption of a minimal coupling between the dark matter (DM) and dark energy (DE) fields introduces significant changes in the predicted evolution of the Universe. Therefore, testing such a possibility constitutes an essential task not only for cosmology but also for fundamental physics. In a previous communication [Phys. Rev. D99, 043521, 2019], we proposed a new null test for the $Λ$CDM model based on the time dependence of the ratio between the DM and DE energy densities which is also able to detect potential signatures of interaction between the dark components. In this work, we extend that analysis avoiding the $ Λ$CDM assumption and reconstruct the interaction in the dark sector in a fully model-independent way using data from type Ia supernovae, cosmic chronometers and baryonic acoustic oscillations. According to our analysis, the $Λ$CDM model is consistent with our model-independent approach at least at $3σ$ CL over the entire range of redshift studied. On the other hand, our analysis shows that the current background data do not allow us to rule out the existence of an interaction in the dark sector. Finally, we present a forecast for next-generation LSS surveys. In particular, we show that Euclid and SKA will be able to distinguish interacting models with about 4\% of precision at $z\approx 1$.

astro-ph.CO↗

arXiv2020

Dark degeneracy I: Dynamical or interacting dark energy?

We revisit the dark degeneracy that arises from the Einstein equations relating geometry to the total cosmic substratum but not resolving its individual components separately. We establish the explicit conditions for the dark degeneracy in the fluid description of the dark sector. At the background level, this degeneracy can be formally understood in terms of a unified dark sector Equation of State (EoS) that depends both on the dynamical nature of the dark energy (DE) as well as on its interaction with the pressureless dark matter. For linear perturbations, the degeneracy arises for specified DE pressure perturbations (or sound speed, equivalently) and DE anisotropic stress. Specializing to the degeneracy between non-interacting dynamical DE and interacting vacuum DE models, we perform a parameter estimation analysis for a range of dynamical DE parametrizations, where for illustration we explicitly break the degeneracy at the linear level by adopting a luminal sound speed for both scenarios. We conduct this analysis using cosmological background data alone and in combination with Planck measurements of the cosmic microwave background radiation. We find that although the overall phenomenology between the dynamical DE and interacting approaches is similar, there are some intriguing differences. In particular, there is an ambiguity in the strength of constraints on $Ω_{m0}$ and $σ_8$, which are considerably weakened for interacting vacuum DE, indicating that the dark degeneracy can change the significance of tensions in cosmological parameters inferred from different data sets.

astro-ph.CO↗

arXiv2018

Null test for interactions in the dark sector

Since there is no known symmetry in Nature that prevents a non-minimal coupling between the dark energy (DE) and cold dark matter (CDM) components, such a possibility constitutes an alternative to standard cosmology, with its theoretical and observational consequences being of great interest. In this paper we propose a new null test on the standard evolution of the dark sector based on the time dependence of the ratio between the CDM and DE energy densities which, in the standard $Λ$CDM scenario, scales necessarily as $a^{-3}$. We use the latest measurements of type Ia supernovae, cosmic chronometers and angular baryonic acoustic oscillations to reconstruct the expansion history using model-independent Machine Learning techniques, namely, the Linear Model formalism and Gaussian Processes. We find that while the standard evolution is consistent with the data at $3σ$ level, some deviations from the $Λ$CDM model are found at low redshifts, which may be associated with the current tension between local and global determinations of $H_0$.

astro-ph.CO↗

arXiv2016

Linear and non-linear perturbations in dark energy models

In this work we discuss observational aspects of three time-dependent parameterisations of the dark energy equation of state $w(z)$. In order to determine the dynamics associated with these models, we calculate their background evolution and perturbations in a scalar field representation. After performing a complete treatment of linear perturbations, we also show that the non-linear contribution of the selected $w(z)$ parameterisations to the matter power spectra is almost the same for all scales, with no significant difference from the predictions of the standard $Λ$CDM model.

astro-ph.CO↗

arXiv2016

Cosmology and Fundamental Physics with the Euclid Satellite

Euclid is a European Space Agency medium class mission selected for launch in 2020 within the Cosmic Vision 2015 2025 program. The main goal of Euclid is to understand the origin of the accelerated expansion of the universe. Euclid will explore the expansion history of the universe and the evolution of cosmic structures by measuring shapes and redshifts of galaxies as well as the distribution of clusters of galaxies over a large fraction of the sky. Although the main driver for Euclid is the nature of dark energy, Euclid science covers a vast range of topics, from cosmology to galaxy evolution to planetary research. In this review we focus on cosmology and fundamental physics, with a strong emphasis on science beyond the current standard models. We discuss five broad topics: dark energy and modified gravity, dark matter, initial conditions, basic assumptions and questions of methodology in the data analysis. This review has been planned and carried out within Euclid's Theory Working Group and is meant to provide a guide to the scientific themes that will underlie the activity of the group during the preparation of the Euclid mission.

astro-ph.CO↗

arXiv2015

Cosmology and fundamental physics with the Euclid satellite

Euclid is a European Space Agency medium class mission selected for launch in 2019 within the Cosmic Vision 2015-2025 programme. The main goal of Euclid is to understand the origin of the accelerated expansion of the Universe. Euclid will explore the expansion history of the Universe and the evolution of cosmic structures by measuring shapes and redshifts of galaxies as well as the distribution of clusters of galaxies over a large fraction of the sky. Although the main driver for Euclid is the nature of dark energy, Euclid science covers a vast range of topics, from cosmology to galaxy evolution to planetary research. In this review we focus on cosmology and fundamental physics, with a strong emphasis on science beyond the current standard models. We discuss five broad topics: dark energy and modified gravity, dark matter, initial conditions, basic assumptions and questions of methodology in the data analysis. This review has been planned and carried out within Euclid's Theory Working Group and is meant to provide a guide to the scientific themes that will underlie the activity of the group during the preparation of the Euclid mission.

astro-ph.CO↗

arXiv2015

Sample variance in N--body simulations and impact on tomographic shear predictions

We study the effects of sample variance in N--body simulations, as a function of the size of the simulation box, namely in connection with predictions on tomographic shear spectra. We make use of a set of 8 $Λ$CDM simulations in boxes of 128, 256, 512 $h^{-1}$Mpc aside, for a total of 24, differing just by the initial seeds. Among the simulations with 128 and 512 $h^{-1}$Mpc aside, we suitably select those closest and farthest from {\it average}. Numerical and linear spectra $P(k,z)$ are suitably connected at low $k$ so to evaluate the effects of sample variance on shear spectra $C_{ij}(\ell)$ for 5 or 10 tomographic bands. We find that shear spectra obtained by using 128 $h^{-1}$Mpc simulations can vary up to $\sim 25\, \%$, just because of the seed. Sample variance lowers to $\sim 3.3\, \%$, when using 512 $h^{-1}$Mpc. These very percentages could however slightly vary, if other sets of the same number of realizations were considered. Accordingly, in order to match the $\sim 1\, \%$ precision expected for data, if still using 8 boxes, we require a size $\sim 1300$ --$ 1700 \, h^{-1}$ Mpc for them.

astro-ph.CO↗

arXiv2015

Effects of Coupled Dark Energy on the Milky Way and its Satellites

We present the first numerical simulations in coupled dark energy cosmologies with high enough resolution to investigate the effects of the coupling on galactic and sub-galactic scales. We choose two constant couplings and a time-varying coupling function and we run simulations of three Milky-Way-size halos ($\sim$10$^{12}$M$_{\odot}$), a lower mass halo (6$\times$10$^{11}$M$_{\odot}$) and a dwarf galaxy halo (5$\times$10$^{9}$M$_{\odot}$). We resolve each halo with several millions dark matter particles. On all scales the coupling causes lower halo concentrations and a reduced number of substructures with respect to LCDM. We show that the reduced concentrations are not due to different formation times, but they are related to the extra terms that appear in the equations describing the gravitational dynamics. On the scale of the Milky Way satellites, we show that the lower concentrations can help in reconciling observed and simulated rotation curves, but the coupling values necessary to have a significant difference from LCDM are outside the current observational constraints. On the other hand, if other modifications to the standard model allowing a higher coupling (e.g. massive neutrinos) are considered, coupled dark energy can become an interesting scenario to alleviate the small-scale issues of the LCDM model.

astro-ph.CO↗

arXiv2015

Physics of the Cosmic Microwave Background Radiation

The cosmic microwave background (CMB) radiation provides a remarkable window onto the early universe, revealing its composition and structure. In these lectures we review and discuss the physics underlying the main features of the CMB.

astro-ph.CO↗

arXiv2014

Structure formation in a $Λ$ $viscous$ CDM universe

The possibility of dark matter being a dissipative component represents an option for the standard view where cold dark matter (CDM) particles behave on large scales as an ideal fluid. By including a physical mechanism to the dark matter description like viscosity we construct a more realistic model for the universe. Also, the known small scale pathologies of the standard CDM model either disappear or become less severe. We study clustering properties of a $Λ$CDM-like model in which dark matter is described as a bulk viscous fluid. The linear power spectrum, the nonlinear spherical "top hat" collapse and the mass functions are presented. We use the analysis with such structure formation tools in order to place an upper bound on the magnitude of the dark matter's viscosity.

astro-ph.CO↗

arXiv2014

Bouncing solutions in Rastall's theory with a barotropic fluid

Rastall's theory is a modification of Einstein's theory of gravity where the covariant divergence of the stress-energy tensor is no more vanishing, but proportional to the gradient of the Ricci scalar. The motivation of this theory is to investigate a possible non-minimal coupling of the matter fields to geometry which, being proportional to the curvature scalar, may represent an effective description of quantum gravity effects. Non-conservation of the stress-energy tensor, via Bianchi identities, implies new field equations which have been recently used in a cosmological context, leading to some interesting results. In this paper we adopt Rastall's theory to reproduce some features of the effective Friedmann's equation emerging from loop quantum cosmology. We determine a class of bouncing cosmological solutions and comment about the possibility of employing these models as effective descriptions of the full quantum theory.

gr-qc↗

arXiv2014

Dark MaGICC: the effect of Dark Energy on galaxy formation. Cosmology does matter

We present the Dark MaGICC project, which aims to investigate the effect of Dark Energy (DE) modeling on galaxy formation via hydrodynamical cosmological simulations. Dark MaGICC includes four dynamical Dark Energy scenarios with time varying equations of state, one with a self-interacting Ratra-Peebles model. In each scenario we simulate three galaxies with high resolution using smoothed particle hydrodynamics (SPH). The baryonic physics model is the same used in the Making Galaxies in a Cosmological Context (MaGICC) project, and we varied only the background cosmology. We find that the Dark Energy parameterization has a surprisingly important impact on galaxy evolution and on structural properties of galaxies at z=0, in striking contrast with predictions from pure Nbody simulations. The different background evolutions can (depending on the behavior of the DE equation of state) either enhance or quench star formation with respect to a LCDM model, at a level similar to the variation of the stellar feedback parameterization, with strong effects on the final galaxy rotation curves. While overall stellar feedback is still the driving force in shaping galaxies, we show that the effect of the Dark Energy parameterization plays a larger role than previously thought, especially at lower redshifts. For this reason, the influence of Dark Energy parametrization on galaxy formation must be taken into account, especially in the era of precision cosmology.

astro-ph.CO↗