arXiv subjects

María Benito

Publications and source records attributed to María Benito.

11 recordsLinked to original sources

arXiv2026

Portrait of a Galaxy on FIRE: Is the $α$-bimodality a natural consequence of inside-out disc growth in a hierarchical formation scenario?

The chemical dichotomy in the [$α$/Fe]-[Fe/H] plane is a consequence of the complex processes underlying the formation and evolution of disc galaxies such as observed in the stellar Milky Way disc. We determine what can drive an $α$-bimodality of the disc in a zoom-in hydrodynamical simulated galaxy which has had no major mergers and negligible radial migration. Using a Milky Way-mass galaxy from the FIRE-2 suite of simulations, we analyse gas flows in the disc together with its star formation and merger history, as well as the chemical evolution of the hot corona, to investigate their connection to transitions in the chemo-dynamical structure of the stellar disc and its radial distribution. The simulated galaxy exhibits high and low-$α$ sequences without having experienced major mergers nor significant radial migration. A high-$α$ thick disc forms during the early chaotic clustering phase. Afterwards, as the star formation rate declines, a dip in the stellar number density appears, coinciding with the dilution of the galactic corona by a minor merger, which subsequently halts the rise of [Fe/H] in the disc. Later, accreted gas onto the disc from minor mergers, mildly enhances the star formation rate and generates the low-$α$ sequence in the outer disc, with radial inward flows of this material feeding the low-$α$ inner disc. Furthermore, we find that even at fixed radii, newly formed stars retain a sizable spread in their chemical abundances, reflecting chemical differences between the in-situ and the infalling gas from which they formed, further indicating that instantaneous gas mixing is invalid. Understanding the chemical evolution of stellar discs requires accounting for their accretion merger history and interaction with the surrounding hot corona, as well as the vertical and radial gas flows that redistribute metals within the disc.

astro-ph.GA↗

arXiv2025

Exploring the Dark Universe: A European Strategy for Axions and other WISPs Discovery

Axions and other very weakly interacting slim (with $m <$ 1 GeV) particles (WISPs) are a common feature of several extensions of the Standard Model of Particle Physics. The search of WISPs was already recommended in the last update of the European strategy on particle physics (ESPP). After that, the physics case for WISPs has gained additional momentum. Indeed, WISPs may provide a new paradigm to explain the nature of dark matter and puzzling astrophysical and particle physics observations. This document briefly summarizes current searches for WISPs and the perspectives in this research field for the next decade, ranging from their theoretical underpinning, over their indirect observational consequences in astrophysics, to their search in laboratory experiments. It is stressed that in Europe a rich, diverse, and low-cost experimental program is already underway with the potential for one or more game-changing discoveries. In this context, it is also reported the role of the EU funded COST Action ''Cosmic WISPers in the Dark Universe: Theory, astrophysics, and experiments'' (CA21106, https://www.cost.eu/actions/CA21106) in coordinating and supporting WISPs searches in Europe, shaping a roadmap to track the strategy to guarantee a European leadership in this field of research. This document has been submitted in March 2025 as an input to the update process of the ESPP.

hep-ph↗

arXiv2025

Fuzzy dark matter fails to explain the dark matter cores

Ultrafaint dwarf galaxies (UFDs) are ideal for studying dark matter (DM) due to minimal baryonic effects. UFD observations suggest cored DM profiles. We find that the core radius -- stellar mass scaling predicted by fuzzy dark matter (FDM) is at $6.1σ$ tension with UFD observations. Combining observations from 27 UFDs, the required FDM mass $m_a = 3.2_{-0.6}^{+0.8}\times 10^{-21}\,{\rm eV}$ is also in conflict with existing Lyman-$α$ bounds. Our results suggest that FDM cannot provide a consistent explanation for DM cores and imply $m_a > 2.2\times 10^{-21}\,{\rm eV}$ at to $2σ$ CL.

astro-ph.CO↗

arXiv2024

On the detection of stellar wakes in the Milky Way: a deep learning approach

Due to poor observational constraints on the low-mass end of the subhalo mass function, the detection of dark matter (DM) subhalos on sub-galactic scales would provide valuable information about the nature of DM. Stellar wakes, induced by passing DM subhalos, encode information about the mass of the inducing perturber and thus serve as an indirect probe for the DM substructure within the Milky Way (MW). Our aim is to assess the viability and performance of deep learning searches for stellar wakes in the Galactic stellar halo caused by DM subhalos of varying mass. We simulate massive objects (subhalos) moving through a homogeneous medium of DM and star particles, with phase-space parameters tailored to replicate the conditions of the Galaxy at a specific distance from the Galactic center. The simulation data is used to train deep neural networks with the purpose of inferring both the presence and mass of the moving perturber, and assess subhalo detectability in varying conditions of the Galactic stellar and DM halos. We find that our binary classifier is able to infer the presence of subhalos, showing non-trivial performance down to a subhalo mass of $5 \times 10^7 \rm \, M_\odot$. We also find that our binary classifier is generalisable to datasets describing subhalo orbits at different Galactocentric distances. In a multiple-hypothesis case, we are able to discern between samples containing subhalos of different masses. Out of the phase-space observables available to us, we conclude that overdensity and velocity divergence are the most important features for subhalo detection performance.

astro-ph.GA↗

arXiv2024

Dark Matter Halo Parameters from Overheated Exoplanets via Bayesian Hierarchical Inference

Dark Matter (DM) can become captured, deposit annihilation energy, and hence increase the heat flow in exoplanets and brown dwarfs. Detecting such a DM-induced heating in a population of exoplanets in the inner kpc of the Milky Way thus provides potential sensitivity to the galactic DM halo parameters. We develop a Bayesian Hierarchical Model to investigate the feasibility of DM discovery with exoplanets and examine future prospects to recover the spatial distribution of DM in the Milky Way. We reconstruct from mock exoplanet datasets observable parameters such as exoplanet age, temperature, mass, and location, together with DM halo parameters, for representative choices of measurement uncertainty and the number of exoplanets detected. We find that detection of $\mathcal{O}(100)$ exoplanets in the inner Galaxy can yield quantitative information on the galactic DM density profile, under the assumption of 10% measurement uncertainty. Even as few as $\mathcal{O}(10)$ exoplanets can deliver meaningful sensitivities if the DM density and inner slope are sufficiently large.

astro-ph.IM↗

arXiv2023

Back to the present: A general treatment for the tidal field from the wake of dynamical friction

Dynamical friction can be a valuable tool for inferring dark matter properties that are difficult to constrain by other methods. Most applications of dynamical friction calculations are concerned with the long-term angular momentum loss and orbital decay of the perturber within its host. This, however, assumes knowledge of the unknown initial conditions of the system. We advance an alternative methodology to infer the host properties from the perturber's shape distortions induced by the tides of the wake of dynamical friction, which we refer to as the tidal dynamical friction. As the shape distortions rely on the tidal field that has a predominantly local origin, we present a strategy to find the local wake by integrating the stellar orbits back in time along with the perturber, then removing the perturber's potential and re-integrating them back to the present. This provides perturbed and unperturbed coordinates and hence a change in coordinates, density, and acceleration fields, which yields the back-reaction experienced by the perturber. The method successfully recovers the tidal field of the wake based on a comparison with N-body simulations. We show that similar to the tidal field itself, the noise and randomness of the dynamical friction force due to the finite number of stars is also dominated by regions close to the perturber. Stars near the perturber influence it more but are smaller in number, causing a high variance in the acceleration field. These fluctuations are intrinsic to dynamical friction. We show that a stellar density of $0.0014 {\rm M_\odot\, kpc^{-3}}$ yields an inherent variance of 10% to the dynamical friction. The current method extends the family of dynamical friction methods that allow for the inference of host properties from tidal forces of the wake. It can be applied to specific galaxies, such as Magellanic Clouds, with Gaia data.

astro-ph.GA↗

arXiv2023

A Bayesian estimation of the Milky Way's circular velocity curve using Gaia DR3

Our goal is to calculate the circular velocity curve of the Milky Way, along with corresponding uncertainties that quantify various sources of systematic uncertainty in a self-consistent manner. The observed rotational velocities are described as circular velocities minus the asymmetric drift. The latter is described by the radial axisymmetric Jeans equation. We thus reconstruct the circular velocity curve between Galactocentric distances from 5 kpc to 14 kpc using a Bayesian inference approach. The estimated error bars quantify uncertainties in the Sun's Galactocentric distance and the spatial-kinematic morphology of the tracer stars. As tracers, we used a sample of roughly 0.6 million stars on the red giant branch stars with six-dimensional phase-space coordinates from Gaia data release 3 (DR3). More than 99% of the sample is confined to a quarter of the stellar disc with mean radial, rotational, and vertical velocity dispersions of $(35\pm 18)\,\rm km/s$, $(25\pm 13)\,\rm km/s$, and $(19\pm 9)\,\rm km/s$, respectively. We find a circular velocity curve with a slope of $0.4\pm 0.6\,\rm km/s/kpc$, which is consistent with a flat curve within the uncertainties. We further estimate a circular velocity at the Sun's position of $v_c(R_0)=233\pm7\, \rm km/s$ and that a region in the Sun's vicinity, characterised by a physical length scale of $\sim 1\,\rm kpc$, moves with a bulk motion of $V_{LSR} =7\pm 7\,\rm km/s$. Finally, we estimate that the dark matter (DM) mass within 14 kpc is $\log_{10}M_{\rm DM}(R<14\, {\rm kpc})/{\rm M_{\odot}}= \left(11.2^{+2.0}_{-2.3}\right)$ and the local spherically averaged DM density is $ρ_{\rm DM}(R_0)=\left(0.41^{+0.10}_{-0.09}\right)\,{\rm GeV/cm^3}=\left(0.011^{+0.003}_{-0.002}\right)\,{\rm M_\odot/pc^3}$. In addition, the effect of biased distance estimates on our results is assessed.

astro-ph.GA↗

arXiv2022

Sensitivity Estimation for Dark Matter Subhalos in Synthetic Gaia DR2 using Deep Learning

The abundance of dark matter (DM) subhalos orbiting a host galaxy is a generic prediction of the cosmological framework, and is a promising way to constrain the nature of DM. In this paper, we investigate the use of machine learning-based tools to quantify the magnitude of phase-space perturbations caused by the passage of DM subhalos. A simple binary classifier and an anomaly detection model are proposed to estimate if stars or star particles close to DM subhalos are statistically detectable in simulations. The simulated datasets are three Milky Way-like galaxies and nine synthetic Gaia DR2 surveys derived from these. Firstly, we find that the anomaly detection algorithm, trained on a simulated galaxy with full 6D kinematic observables and applied on another galaxy, is nontrivially sensitive to the DM subhalo population. On the other hand, the classification-based approach is not sufficiently sensitive due to the extremely low statistics of signal stars for supervised training. Finally, the sensitivity of both algorithms in the Gaia-like surveys is negligible. The enormous size of the Gaia dataset motivates the further development of scalable and accurate data analysis methods that could be used to select potential regions of interest for DM searches to ultimately constrain the Milky Way's subhalo mass function, as well as simulations where to study the sensitivity of such methods under different signal hypotheses.

astro-ph.GA↗

arXiv2021

Cooling process of brown dwarfs in Palatini f(R) gravity

We present an analytical model for the evolution of brown dwarfs in quadratic Palatini f(R) gravity. We improve previous studies by adopting a more realistic description of the partially-degenerate state that characterizes brown dwarfs. Furthermore, we take into account the hydrogen metallic-molecular phase transition between the interior of the brown dwarf and its photosphere. For such improved model, we revise the cooling process of sub-stellar objects.

gr-qc↗

arXiv2020

Tidal forces from the wake of dynamical friction: warps, lopsidedness and kinematic misalignment

A galaxy moving through a background of dark matter particles, induces an overdensity of these particles or a wake behind it. The back reaction of this wake on the galaxy is a force field that can be decomposed into an effective deceleration (called dynamical friction) and a tidal field. In this paper we determine the tidal forces, thus generated on the galaxy, and the resulting observables, which are shown to be warps, lopsidedness and/or kinematic-photometric position angle misalignments. We estimate the magnitude of the tidal-like effects needed to reproduce the observed warp and lopsidedness on the isolated galaxy IC 2487. Within a realistic range of dark matter distribution properties the observed warped and lopsided kinematical properties of IC 2487 is possible to reproduce (the background medium of dark matter particles has a velocity dispersion of $\lesssim 80\,{\rm km\,s^{-1}}$ and the density $10^4-10^5~{\rm M_\odot\,kpc^{-3}}$, more likely at the lower end). We conclude that the proposed mechanism can generate warps, lopsidedness and misalignments observed in isolated galaxies or galaxies in loose groups. The method can be used also to constrain dark matter spatial and velocity distribution properties.

astro-ph.GA↗

arXiv2020

Implications of Milky Way Substructures for the Nature of Dark Matter

We study how the indirect observation of dark matter substructures in the Milky Way, using recent stellar stream studies, translates into constraints for different dark matter models. Particularly, we use the measured number of dark subhalos in the mass range $10^7-10^9\,{\rm M_{\odot}}$ to constrain modifications of the subhalo mass function compared to the cold dark matter scenario. We obtain the lower bounds $m_{\rm WDM} > 3.2\,{\rm keV}$ and $m_{\rm FDM} > 5.2\times 10^{-21}\,{\rm eV}$ on the warm dark matter and fuzzy dark matter particle mass, respectively. When dark matter is coupled to a dark radiation bath, we find that kinetic decoupling must take place at temperatures higher than $T_{\rm kd} > 0.7\,{\rm keV}$. We also discuss future prospects of stellar stream observations.

astro-ph.CO↗