arXiv subjects

Jorge Sarrato-Alós

Publications and source records attributed to Jorge Sarrato-Alós.

6 recordsLinked to original sources

arXiv2026

Dark matter haloes from dwarf to massive galaxies: no systematic inner-density tension with ΛCDM hydrodynamical simulations

Two of the most prominent small-scale challenges to the cold dark matter (CDM) paradigm are the cusp-core and diversity-of-rotation-curves problems. The former concerns the shallow inner DM density profiles inferred for many galaxies compared with the cusps predicted by collisionless CDM, while the latter concerns the wider range of inner DM densities and rotation curve shapes inferred observationally than hydrodynamical simulations traditionally reproduce. Robust observational constraints on DM core sizes and halo densities are therefore essential for testing both the nature of DM and the impact of galaxy formation processes. We analyse the inner DM distribution of a curated sample of 48 gas-rich galaxies and 8 Milky Way gas-poor satellites, spanning 6 orders of magnitude in $M_\ast$. We find substantial scatter in DM core sizes and degrees of coreness, with both cuspy and cored haloes occurring over a broad $M_\ast$ range. The cores are energetically consistent with stellar feedback, requiring modest supernova energy coupling efficiencies of order $0.1-1\%$. Comparisons with the NIHAO, FIRE-2, and EDGE simulations reveal broad agreement in the inner DM densities and logarithmic slopes of observed and simulated galaxies. The main residual differences concern the steep slopes of some massive simulated galaxies and differences in SHMRs. Using a rotation-curve diversity diagnostic from previous work, we find that extreme discrepancies with simulations are absent from our curated sample and largely attributable to uncertain kinematics or baryonic mass distributions. Within the scope of our analysis, we find no evidence of a systematic inner-density tension between our galaxy sample and current $Λ$CDM hydrodynamical simulations. Together with the modest energetic requirements for core formation, this substantially alleviates the cusp-core and diversity-of-rotation-curves problems.

astro-ph.GA↗

arXiv2026

Dark matter density profiles of the Milky Way satellite population: reconciling simulations and observations

The cusp-core problem remains a key challenge for the $Λ$CDM model. Historically, comparing inner dark matter halo slopes ($d\logρ/d\log r$) from simulations and observations has suffered from a methodological mismatch: evaluating slopes at different radii creates apparent tensions due to inconsistent definitions rather than genuine physical differences. We rigorously compare dark matter density profiles of Milky Way (MW) dwarf satellites inferred from dynamical modelling against CDM hydrodynamical simulations. Using the NIHAO and FIRE-2 suites ($M_{\star} \sim 10^3$-$10^{11}\,\rm M_\odot$), we confront simulated profiles with dynamical inferences of 16 MW satellites across four methods, strictly within their reliability limits. Crucially, we evaluate simulated slopes at observationally accessible radii, directly comparing profiles at matched stellar mass. Both observed and simulated galaxies exhibit a mass-dependent core-formation trend: inner slopes rise from cuspy values ($\approx -1.5$) at $M_{\star} \sim 10^5\,\rm M_\odot$ to core-like values ($\approx 0$ to $-0.4$) at $M_{\star} \sim 10^8\,\rm M_\odot$. Efficient core formation begins at $M_{\star} \gtrsim 10^6\,\rm M_\odot$ for centrals, where satellites display increased scatter consistent with tidal disruption. Simulated profiles agree with observations within $\lesssim 1σ$ for most systems, outperforming a NFW profile. Furthermore, differing observational models present scatter for a given system comparable to the simulation-to-observation offset. Evaluating dark matter density slopes at fixed physical radii significantly improves agreement between hydrodynamical simulations and dynamical models, revealing no clear tension when comparing profiles at fixed stellar mass, but Willman\,1 remains an unresolved outlier.

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arXiv2026

The Impact of Star Formation Histories on the Inner Dark Matter Density Slopes of Galaxies

Aims. We aim to investigate the connection between star formation histories (SFHs) and the inner dark matter density profiles of simulated galaxies. In particular, we test whether the burstiness and temporal distribution of star formation influence the formation of cored versus cuspy dark matter profiles. Methods. We homogeneously analysed simulated galaxies from the NIHAO and FIRE-2 projects. For each galaxy, we derived dark matter density profiles and measured the logarithmic slope in the inner region of the dark matter halo (1-2% of R$_{\rm vir}$). To characterise star formation burstiness, we introduced a criterion based on comparing the star formation rate (SFR) averaged over two distinct timescales. We further quantified the temporal concentration of SFHs by computing $M_{\star, \rm post}$ / $M_{\star, \rm pre}$, the ratio of stellar mass formed after versus before the epoch of reionisation at redshift z $\sim$ 6.5. Results. Homogeneous analysis reveals that inner slope versus stellar-to-halo mass ratio trends for NIHAO and FIRE-2 galaxies are in much better agreement than reported in previous works. The burstiness and post-to-pre reionisation stellar mass ratio of the SFH explain the scatter in the inner slope versus stellar-to-halo mass ratio relation, revealing that galaxies with above average burstiness and more extended SFHs are more efficient at developing cored dark matter profiles. In contrast, galaxies with smoother SFHs and earlier stellar mass assembly tend to maintain cuspier dark matter profiles. We present an analytic expression that improves predictions for the inner slope using the parameter $M_{\star \rm,post}$ / $M_{\star \rm,pre}$, which reduces the mean squared error in both simulation suites relative to previous formulations based solely on the stellar-to-halo mass ratio.

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arXiv2025

Beyond single tracers: CNN-based inference of galaxy mass profiles from combined gas and stellar kinematics

We investigate whether combining gas and stellar kinematic maps provides measurable advantages in recovering galaxy mass profiles, compared to using single-component maps alone. While traditional methods struggle to integrate multi-tracer data effectively, we test whether deep learning models can leverage this joint information. We develop a probabilistic convolutional neural network (CNN) framework trained and tested on mock galaxy kinematic maps from multiple cosmological simulation suites. Our model is trained on gas-only, stars-only, and combined gas+stellar velocity maps, allowing direct comparison of performance across tracers. To assess robustness, we include simulations with differing feedback models and galaxy properties. Combining gas and stellar maps reduces the dispersion in the inferred mass profiles by up to a factor of $\sim$1.5 compared to models using either tracer independently. The CNN architecture effectively captures complementary information from the two components. However, we find limitations in generalizing between simulation suites, with reduced performance when applying models trained on one suite to galaxies from another.

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arXiv2025

Galaxy mass profiles with convolutional neural networks

Determining the dynamical mass profiles of dispersion-supported galaxies is particularly challenging due to projection effects and the unknown shape of their velocity anisotropy profile. Our goal is to develop a machine learning algorithm capable of recovering dynamical mass profiles of dispersion-supported galaxies from line-of-sight stellar data. Traditionally, this task relies on time-consuming methods that require profile parameterization and assume dynamical equilibrium and spherical symmetry. We train a convolutional neural network model using various sets of cosmological hydrodynamical simulations of galaxies. By extracting projected stellar data from the simulated galaxies and feeding it into the model, we obtain the posterior distribution of the dynamical mass profile at ten different radii. Additionally, we evaluate the performance of existing literature mass estimators on our dataset. Our model achieves more accurate results than any literature mass estimator while also providing enclosed mass estimates at radii where no previous estimators exist. We confirm that the posterior distributions produced by the model are well-calibrated, ensuring they provide meaningful uncertainties. However, issues remain, as the method loses performance when trained on one set of simulations and applied to another, highlighting the importance of improving the generalization of ML methods trained on specific galaxy simulations.

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arXiv2023

Constraining gas metal mixing strength in simulations using observations of the Milky Way's disc

This work explores the mixing rate of metals in the interstellar medium (ISM), comparing observational constraints from our solar neighbourhood to high resolution cosmological hydrodynamical simulations of Milky Way (MW)-like galaxies. The mixing rate, described by the coefficient C, is varied in simulations between 0 and 0.05, with resultant simulated galaxies compared to observations of metallicity dispersion in young star clusters, HII regions and neutral gas in the disc of the MW. A value of C between 0.003125 and 0.0125 is found to self-consistently match a range of observables, with a best estimate of C=0.0064$\pm$0.0004. We demonstrate that the relationship between metal dispersion in young stars, HII regions and neutral gas, versus the coefficient C, can be described by a power law. These constrained mixing rates infer a comparatively well mixed ISM in the solar neighbourhood, at odds with some recent observations that have reported a highly inhomogeneous ISM. The degree of mixing suggested by this work is lower than what often employed in many hydrodynamical simulations. Our results have implications for studying the metallicity distribution of stars as well as of gas in the interstellar and circumgalactic media.

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