arXiv subjects

Nelson D. Padilla

Publications and source records attributed to Nelson D. Padilla.

At least 19 recordsLinked to original sources

arXiv2026

The properties of central stellar knots embedded in galactic bulges of CIELO simulations

Deeply bound stellar substructures of about 1 kpc at the center of bulges are found in a subset of galaxies from the cosmological chemo-hydrodynamical zoom-in CIELO simulation suite. They were identified as stellar overdensities at the lowest binding energies in each galaxy's circularity-energy $(ε, E)$ plane. We refer to these overdensities as stellar knots. We aim to characterize their properties in the context of bulge assembly using CIELO simulated galaxies spanning a wide range of stellar masses ($10^{8.0}$-$10^{10.7}\,\mathrm{M}_{\odot}$), with diverse formation histories. We inspect 54 galactic bulges. Within them, we isolate stellar knot candidates in $(ε, E)$ space, and identify 28 robust knots satisfying successive selection criteria: kinematic, concentration, and morphology. We characterize their chemical enrichment, formation timescales, formation sites, progenitor gas origin, and spatial distributions. Across all galaxy masses, knots are systematically alpha-element enhanced, having assembled the bulk of their stellar mass at earlier epochs and on shorter timescales than other bulge populations, with a median of $\sim$2$\,$Gyr versus $\sim$5$\,$Gyr. Regarding their origin, knots are predominantly in-situ ($5\%$ accreted mass fraction, roughly half that of the rest of the bulge), with negligible disk-born stars contribution and the largest gas fractions originating from a primordial central spheroid ($21\%$ versus 16--17$\%$ for the surrounding populations), consistent with being the primary gas fuel for the alpha-element enhancement. In terms of structure, knots exhibit a variety of morphologies, with spheroidal shapes predominating. Dynamical selection in $(ε, E)$ space of CIELO galaxies demonstrates its effectiveness in recovering coeval stellar populations, pointing to stellar knots as plausible fossil signatures of early in-situ bulge assembly.

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arXiv2025

Aletheia: Emulating the non-linear matter power spectrum in the context of evolution mapping

We present Aletheia, a new emulator of the non-linear matter power spectrum, $P(k)$, built upon the evolution mapping framework. This framework addresses the limitations of traditional emulation by focusing on $h$-independent cosmological parameters, which can be separated into those defining the linear power spectrum shape ($\mathbfΘ_{\mathrm{s}}$) and those affecting only its amplitude evolution ($\mathbfΘ_{\mathrm{e}}$). The combined impact of evolution parameters and redshift is compressed into a single amplitude parameter, $σ_{12}$. Aletheia uses a two-stage Gaussian Process emulation: a primary emulator predicts the non-linear boost factor as a function of ($\mathbfΘ_{\mathrm{s}}$) and $σ_{12}$ for fixed evolution parameters, while a second one applies a small linear correction based on the integrated growth history. The emulator is trained on shape parameters spanning $\pm$5$σ$ of Planck constraints and a wide clustering range $0.2 < σ_{12} < 1.0$, providing predictions for $0.006\,{\rm Mpc}^{-1} < k < 2\,{\rm Mpc}^{-1}$. We validate Aletheia against N-body simulations, demonstrating sub-percent accuracy. When tested on a suite of dynamic dark energy models, the full emulator's predictions show a variance of approximately 0.2%, a factor of five smaller than that of the state-of-the-art EuclidEmulator2 (around 1% variance). Furthermore, Aletheia maintains sub-percent accuracy for the best-fit dynamic dark energy cosmology from recent DESI data, a model whose parameters lie outside the training ranges of most conventional emulators. This demonstrates the power of the evolution mapping approach, providing a robust and extensible tool for precision cosmology.

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arXiv2025

Insight into the physical processes that shape the metallicity profiles in galaxies

The distribution of chemical elements in the star-forming regions can store information on the chemical enrichment history of the galaxies. Negative metallicity gradients are expected in galaxies forming inside-out. However, observations show that the metallicity profiles can be broken. We aim to study the diversity of metallicity profiles that can arise in the current cosmological context and compare them with available observations. We also seek to identify the physical processes responsible for breaks in metallicity profiles by using two galaxies as case studies. We analyze central galaxies from the cosmological simulations of the CIELO project, within the stellar mass range [$10^{8.5}$, $10^{10.5}$] M$_\odot$ at $z=0$. A new algorithm, DB-A, was developed to fit multiple power laws to the metallicity profiles, enabling a flexible assessment of metallicity gradients in various galactic regions. The simulations include detailed modeling of gas, metal-dependent cooling, star formation, and supernova feedback. At $z=0$, we find diverse profile shapes, including inner and outer drops and rises, with some galaxies exhibiting double breaks. Gradient values align with observations. A temporal analysis of Local Group analogs shows inner and outer breaks occurring at all cosmic times, with outer breaks being more frequent. Metallicity gradients show high variability at high redshift, transitioning to mild evolution at lower redshift. Most inner breaks show central oxygen enhancement, linked to gas accretion and star formation. Inner drops result from disrupted gas due to feedback-driven outflows. Outer breaks with high metallicities arise from re-accreted material, extended star formation, and CGM-driven gas mixing. Outer drops are common at high redshift, linked to metal-poor gas accretion from cold flows. We highlight the complex interplay of these processes which often act together.

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arXiv2024

Gravitational to Coulomb force ratio and the origin of the Cosmic magnetic field

The origin of the seeds of galactic magnetic fields is a subject that remains under debate. Here we will explore a simple source based on tiny charge asymmetries in slowly rotating protogalaxies. We use current knowledge of galaxy formation and evolution to estimate that a charge imbalance of $1$ every $\sim 10^{38\pm 5}$ charge carriers in slowly rotating protogalaxies can provide adequate seeds for the galactic dynamos. Interestingly, this is of the same order than the ratio of gravitational to Coulomb forces between the elementary plasma constituents. Motivated by this fact, we study different mechanisms for generating such charge imbalances from a direct interplay of gravitational and Coulomb forces, namely the possibility that these are of primordial origin, that stellar or primordial black holes redistribute charge in protogalaxies, or that the imbalance is sourced by gravity as the galaxy forms in quasi-hydrostatic equilibrium. Our results show that primordial asymmetries drop to small values by the onset of galaxy formation, with an amplitude that is similar to the possible charge asymmetries that could be produced by black holes. Although these charge asymmetries can have values within the range of interest, they are much smaller than the gravitationally induced one in hydrostatic equilibrium conditions. The latter lies in the upper range of the required charge imbalance.

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arXiv2024

The electric charge of black holes within galaxies

We present improved estimates of the electric charge that black holes could hold when these are embedded in the ionised plasma within galaxies. We have implemented the spontaneous emission of charges of opposite sign to that of the black hole via athermal Hawking evaporation, including its dependence on black hole spin, and we have estimated the equilibrium charge that arises as this charge loss is balanced by the continuous accretion of charges from the surrounding plasma. The resulting charge can be several orders of magnitude lower than previously estimated upper limits, but it can surpass the pair production limit noted by Gibbons (1974) by a margin that increases with the amplitude of the black hole spin and the density of the plasma. We also implement a calculation for the net charge of galaxies due to their stellar black holes and to primordial black holes in the case these make up a fraction of the dark matter. We find that these charges lie within the range that would produce adequate magnetic field seeds at the onset of galaxy formation.

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arXiv2024

A new test of gravity -- II: Application of marked correlation functions to luminous red galaxy samples

We apply the marked correlation function test proposed by Armijo et al. (Paper I) to samples of luminous red galaxies (LRGs) from the final data release of the Sloan Digital Sky Survey (SDSS) III. The test assigns a density-dependent mark to galaxies in the estimation of the projected marked correlation function. Two gravity models are compared: general relativity (GR) and $f(R)$ gravity. We build mock catalogues which, by construction, reproduce the measured galaxy number density and two-point correlation function of the LRG samples, using the halo occupation distribution model (HOD). A range of HOD models give acceptable fits to the observational constraints, and this uncertainty is fed through to the error in the predicted marked correlation functions. The uncertainty from the HOD modelling is comparable to the sample variance for the SDSS-III LRG samples. Our analysis shows that current galaxy catalogues are too small for the test to distinguish a popular $f(R)$ model from GR. However, upcoming surveys with a better measured galaxy number density and smaller errors on the two-point correlation function, or a better understanding of galaxy formation, may allow our method to distinguish between viable gravity models.

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arXiv2024

A new test of gravity -- I: Introduction to the method

We introduce a new scheme based on the marked correlation function to probe gravity using the large-scale structure of the Universe. We illustrate our approach by applying it to simulations of the metric-variation $f(R)$ modified gravity theory and general relativity (GR). The modifications to the equations in $f(R)$ gravity lead to changes in the environment of large-scale structures that could, in principle, be used to distinguish this model from GR. Applying the Monte Carlo Markov Chain algorithm, we use the observed number density and two-point clustering to fix the halo occupation distribution (HOD) model parameters and build mock galaxy catalogues from both simulations. To generate a mark for galaxies when computing the marked correlation function we estimate the local density using a Voronoi tessellation. Our approach allows us to isolate the contribution to the uncertainty in the predicted marked correlation function that arises from the range of viable HOD model parameters, in addition to the sample variance error for a single set of HOD parameters. This is critical for assessing the discriminatory power of the method. In a companion paper we apply our new scheme to a current large-scale structure survey.

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arXiv2023

Galaxy evolution in modified gravity simulations: using passive galaxies to constrain gravity with upcoming surveys

We present a quantitative analysis of the properties of galaxies and structures evolving in universes dominated by different modified gravitational models, including two variants of the f(R)-gravity (F) and two of the Dvali-Gabdadze-Poratti (N) braneworld model, which respectively feature the chameleon and Vainshtein screening mechanisms. Using the Simulation HYdrodynamics BeyONd Einstein (SHYBONE) cosmological hydrodynamical full-physics simulations suite, we study the departures in the properties of galaxies residing in different environments with respect to the standard model (GR). Using two different criteria to compare, we find that structures formed within modified gravity tend to show a denser gas density profile than their GR counterparts. Within the different modified gravity models, N1 and F5 gravity models show greater departures from the standard model, with gas density profiles $ρ_{\rm IGM} \geq 30\%$ denser in the outskirts for the N1 model, and in the inner parts for the F5 model. Additionally, we find that haloes evolving in MG universes show, in general, larger quenched fractions than GR, reaching up to $20\%$ larger quenching fractions in F5 regardless of the stellar mass of the galaxy. With respect to the other models, F6, N1 and N5 show slightly larger quenched fractions, but no strong differences can be found. These results directly impact the colour distribution of galaxies, making them in MG models redder and older than their GR counterparts. Like GR, once the environment starts to play a role, galaxies rapidly get quenched and the differences between models vanish.

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arXiv2023

Too dense to go through: The importance of low-mass clusters for satellite quenching

We study the evolution of satellite galaxies in clusters of the \textsc{c-eagle} simulations, a suite of 30 high-resolution cosmological hydrodynamical zoom-in simulations based on the \textsc{eagle} code. We find that the majority of galaxies that are quenched at $z=0$ ($\gtrsim$ 80$\%$) reached this state in a dense environment (log$_{10}$M$_{200}$[M$_{\odot}$]$\geq$13.5). At low redshift, regardless of the final cluster mass, galaxies appear to reach their quenching state in low-mass clusters. Moreover, galaxies quenched inside the cluster that they reside in at $z=0$ are the dominant population in low-mass clusters, while galaxies quenched in a different halo dominate in the most massive clusters. When looking at clusters at $z>0.5$, their in situ quenched population dominates at all cluster masses. This suggests that galaxies are quenched inside the first cluster they fall into. After galaxies cross the cluster's $r_{200}$ they rapidly become quenched ($\lesssim$ 1Gyr). Just a small fraction of galaxies ($\lesssim 15\%$) is capable of retaining their gas for a longer period of time, but after 4Gyr, almost all galaxies are quenched. This phenomenon is related to ram pressure stripping and is produced when the density of the intracluster medium reaches a threshold of $ρ_{\rm ICM}$ $\sim 3 \times 10 ^{-5}$ n$_{\rm H}$ (cm$^{-3}$). These results suggest that galaxies start a rapid-quenching phase shortly after their first infall inside $r_{200}$ and that, by the time they reach $r_{500}$, most of them are already quenched.

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arXiv2023

Not Hydro: Using Neural Networks to estimate galaxy properties on a Dark-Matter-Only simulation

Using data from TNG300-2, we train a neural network (NN) to recreate the stellar mass ($M^*$) and star formation rate (SFR) of central galaxies in a dark-matter-only simulation. We consider 12 input properties from the halo and sub-halo hosting the galaxy and the near environment. $M^*$ predictions are robust, but the machine does not fully reproduce its scatter. The same happens for SFR, but the predictions are not as good as for $M^*$. We chained neural networks, improving the predictions on SFR to some extent. For SFR, we time-averaged this value between $z=0$ and $z=0.1$, which improved results for $z=0$. Predictions of both variables have trouble reproducing values at lower and higher ends. We also study the impact of each input variable in the performance of the predictions using a leave-one-covariate-out approach, which led to insights about the physical and statistical relation between input variables. In terms of metrics, our machine outperforms similar studies, but the main discoveries in this work are not linked with the quality of the predictions themselves, but to how the predictions relate to the input variables. We find that previously studied relations between physical variables are meaningful to the machine. We also find that some merger tree properties strongly impact the performance of the machine. %We highlight the value of machine learning (ML) methods in helping understand the information contained in different variables, since with its help we were able to obtain useful insights resulting from studying the impact of input variables on the resulting behaviour of galaxy properties. We conclude that ML models are useful tools to understand the significance of physical different properties and their impact on target characteristics, as well as strong candidates for potential simulation methods.

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arXiv2023

Guess the cheese flavour by the size of its holes: A cosmological test using the abundance of Popcorn voids

We present a new definition of cosmic void and a publicly available code with the algorithm that implements it. Underdense regions are defined as free-form objects, called popcorn voids, made from the union of spheres of maximum volume with a given joint integrated underdensity contrast.The method is inspired by the excursion-set theory and consequently no rescaling processing is needed, the removal of overlapping voids and objects with sizes below the shot noise threshold is inherent in the algorithm. The abundance of popcorn voids in the matter field can be fitted using the excursion-set theory provided the relationship between the linear density contrast of the barrier and the threshold used in void identification is modified relative to the spherical evolution model. We also analysed the abundance of voids in biased tracer samples in redshift space. We show how the void abundance can be used to measure the geometric distortions due to the assumed fiducial cosmology, in a test similar to an Alcock-Paczyński test. Using the formalism derived from previous works, we show how to correct the abundance of popcorn voids for redshift-space distortion effects. Using this treatment, in combination with the excursion-set theory, we demonstrate the feasibility of void abundance measurements as cosmological probes. We obtain unbiased estimates of the target parameters, albeit with large degeneracies in the parameter space. Therefore, we conclude that the proposed test in combination with other cosmological probes has potential to improve current cosmological parameter constraints.

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arXiv2023

Dark matter from primordial black holes would hold charge

We explore the possibility that primordial black holes (PBHs) contain electric charge down to the present day. We find that PBHs should hold a non-zero net charge at their formation, due to either Poisson fluctuations at horizon crossing or high-energy particle collisions. Although initial charge configurations are subject to fast discharge processes through particle accretion or quantum particle emission, we show that maximally rotating PBHs could produce magnetic fields able to shield them from discharge. Moreover, given that electrons are the lightest and fastest charge carriers, we show that the plasma within virialised dark matter haloes can endow PBHs with net negative charge. We report charge-to-mass ratios between $10^{-31}\,C/\mbox{kg}$ and $10^{-15}\,C/\mbox{kg}$ for PBHs within the mass windows that allow them to constitute the entirety of the dark matter in the Universe.

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arXiv2023

Extended primordial black hole mass functions with a spike

We introduce a modification of the Press-Schechter formalism aimed to derive general mass functions for primordial black holes (PBHs). In this case, we start from primordial power spectra (PPS) which include a monochromatic spike, typical of ultra slow-roll inflation models. We consider the PBH formation as being associated to the amplitude of the spike on top of the linear energy density fluctuations, coming from a PPS with a blue index. By modelling the spike with a log-normal function, we study the properties of the resulting mass function spikes, and compare these to the underlying extended mass distributions. When the spike is at PBH masses which are much lower than the exponential cutoff of the extended distribution, very little mass density is held by the PBHs within the spike, and it is not ideal to apply the Press-Schechter formalism in this case as the resulting characteristic overdensity is too different from the threshold for collapse. It is more appropriate to do so when the spike mass is similar to, or larger than the cutoff mass. Additionally, it can hold a similar mass density as the extended part. Such particular mass functions also contain large numbers of small PBHs, especially if stable PBH relics are considered, and they can provide $\sim 1000M_\odot$ seeds for the supermassive black holes at the centres of present-day galaxies. The constraints on the fraction of dark matter in PBHs for monochromatic mass functions are somewhat relaxed when there is an additional underlying extended distribution of masses.

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arXiv2022

A deep learning approach to halo merger tree construction

A key ingredient for semi-analytic models (SAMs) of galaxy formation is the mass assembly history of haloes, encoded in a tree structure. The most commonly used method to construct halo merger histories is based on the outcomes of high-resolution, computationally intensive N-body simulations. We show that machine learning (ML) techniques, in particular Generative Adversarial Networks (GANs), are a promising new tool to tackle this problem with a modest computational cost and retaining the best features of merger trees from simulations. We train our GAN model with a limited sample of merger trees from the Evolution and Assembly of GaLaxies and their Environments (EAGLE) simulation suite, constructed using two halo finders-tree builder algorithms: SUBFIND-D-TREES and ROCKSTAR-ConsistentTrees. Our GAN model successfully learns to generate well-constructed merger tree structures with high temporal resolution, and to reproduce the statistical features of the sample of merger trees used for training, when considering up to three variables in the training process. These inputs, whose representations are also learned by our GAN model, are mass of the halo progenitors and the final descendant, progenitor type (main halo or satellite) and distance of a progenitor to that in the main branch. The inclusion of the latter two inputs greatly improves the final learned representation of the halo mass growth history, especially for SUBFIND-like ML trees. When comparing equally sized samples of ML merger trees with those of the EAGLE simulation, we find better agreement for SUBFIND-like ML trees. Finally, our GAN-based framework can be utilised to construct merger histories of low- and intermediate-mass haloes, the most abundant in cosmological simulations.

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arXiv2022

Evolution mapping: a new approach to describe matter clustering in the non-linear regime

We present a new approach to describe statistics of the non-linear matter density field that exploits a degeneracy in the impact of different cosmological parameters on the linear dimensionless matter power spectrum, $Δ^2_{\rm L}(k)$. We classify all cosmological parameters into two groups, shape parameters, which determine the shape of $Δ^2_{\rm L}(k)$, and evolution parameters, which only affect its amplitude at any given redshift. With this definition, the time evolution of $Δ^2_{\rm L}(k)$ in models with identical shape parameters but different evolution parameters can be mapped from one to the other by relabelling the redshifts that correspond to the same clustering amplitude, which we characterize by the linear mass fluctuation in spheres of radius $12\,{\rm Mpc}$, $σ_{12}(z)$. We use N-body simulations to show that the same evolution mapping relation gives a good description of the non-linear power spectrum, the halo mass function, or the full density field. The deviations from the exact degeneracy are the result of the different structure formation histories experienced by each model to reach the same clustering amplitude and can be accurately described in terms of differences in the suppression factor $g(a) = D(a)/a$. These relations can be used to drastically reduce the number of parameters required to describe the cosmology dependence of the power spectrum. We show how this can help to speed up the inference of parameter constraints from cosmological observations. We also present a new design of an emulator of the non-linear power spectrum whose predictions can be adapted to an arbitrary choice of evolution parameters and redshift.

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arXiv2022

The origin of star-gas misalignments in simulated galaxies

We study the origin of misalignments between the stellar and star-forming gas components of simulated galaxies in the EAGLE simulations. We focus on galaxies with stellar masses $\geq 10^9$ M$_\odot$ at 0$\leq$z$\leq$1. We compare the frequency of misalignments with observational results from the SAMI survey and find that overall, EAGLE can reproduce the incidence of misalignments in the field and clusters, as well as the dependence on stellar mass and optical colour within the uncertainties. We study the dependence on kinematic misalignments with internal galaxy properties and different processes related to galaxy mergers and sudden changes in stellar and star-forming gas mass. We found that despite the environment being relevant in setting the conditions to misalign the star-forming gas, the internal galaxy properties play a crucial role in determining whether the gas quickly aligns with the stellar component or not. Hence, galaxies that are more triaxial and more dispersion dominated display more misalignments because they are inefficient at realigning the star-forming gas towards the stellar angular momentum vector.

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arXiv2022

Redshift-space effects in voids and their impact on cosmological tests. Part II: the void-galaxy cross-correlation function

This is the second part of a thorough investigation of the redshift-space effects that affect void properties and the impact they have on cosmological tests. Here, we focus on the void-galaxy cross-correlation function, specifically, on the projected versions that we developed in a previous work. The pillar of the analysis is the one-to-one relationship between real and redshift-space voids above the shot-noise level identified with a spherical void finder. Under this mapping, void properties are affected by three effects: (i) a systematic expansion as a consequence of the distortions induced by galaxy dynamics, (ii) the Alcock-Paczynski volume effect, which manifests as an overall expansion or contraction depending on the fiducial cosmology, and (iii) a systematic off-centring along the line of sight as a consequence of the distortions induced by void dynamics. We found that correlations are also affected by an additional source of distortions: the ellipticity of voids. This is the first time that distortions due to the off-centring and ellipticity effects are detected and quantified. With a simplified test, we verified that the Gaussian streaming model is still robust provided all these effects are taken into account, laying the foundations for improvements in current models in order to obtain unbiased cosmological constraints from spectroscopic surveys. Besides this practical importance, this analysis also encodes key information about the structure and dynamics of the Universe at the largest scales. Furthermore, some of the effects constitute cosmological probes by themselves, as is the case of the void ellipticity.

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arXiv2021

Making use of sub-resolution halos in N-body simulations

Conservative mass limits are often imposed on the dark matter halo catalogues extracted from N-body simulations. By comparing simulations with different mass resolutions, at $z=0$ we find that even for halos resolved by 100 particles, the lower resolution simulation predicts a cumulative halo abundance that is 5 per cent lower than in the higher resolution simulation. We propose a simple weighting scheme to utilise the halos that are usually regarded as being `sub-resolution'. With the scheme, we are able to use halos which contain only 11 particles to reproduce the clustering measured in the higher resolution simulation to within 5 per cent on scales down to $2 h^{-1}$ Mpc, thereby extending the useful halo resolution by a factor of ten below the mass at which the mass functions in the two simulations first start to deviate. The performance of the method is slightly worse at higher redshift. Our method allows a simulation to be used to probe a wider parameter space in clustering studies, for example, in a halo occupation distribution analysis. This reduces the cost of generating many simulations to estimate the covariance matrix on measurements or using a larger volume simulation to make large-scale clustering predictions.

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