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Raúl E. Angulo

Publications and source records attributed to Raúl E. Angulo.

15 recordsLinked to original sources

A 1% accurate method to include baryonic effects in galaxy-galaxy lensing models

Galaxy clustering and galaxy-galaxy lensing are two of the main observational probes in Stage-IV large-scale structure surveys. Unfortunately, the complicated relationship between galaxies and matter limits the exploitation of this data. Galaxy bias models -- such as the hybrid Lagrangian bias expansion -- allow describing galaxy clustering down to scales as small as $k = 0.7h$/Mpc. However, the galaxy-matter cross-power spectra are already affected by baryons on these scales, directly impacting the modelling of galaxy-galaxy lensing. We propose to extend models of the galaxy-matter cross-power spectrum $P_{\rm gm}(k)$ (currently only accounting for dark matter) by including a baryonic correction inferred from the matter component ($S_{\rm mm}(k)$), so that $P_{\rm gm, full \, physics} (k) = \sqrt{S_{\rm mm}} P_{\rm gm, gravity \, only}$. We use the FLAMINGO simulations to measure the effect of baryons on the galaxy-matter cross-power spectrum and to assess the performance of our model. We perform a Bayesian analysis of synthetic data, implementing a model based on BACCO's hybrid Lagrangian bias expansion (for the nonlinear galaxy bias) and Baryon Correction Model. Ignoring baryons in the galaxy-matter cross-power spectrum leads to a biased inference of the galaxy bias, while ignoring baryons in both the galaxy-matter and matter-matter power spectra leads to a biased inference of both the galaxy bias and cosmological parameters. In contrast, our method is 1% accurate compared to all physics variations in FLAMINGO and on all scales described by hybrid perturbative models ($k < 0.7h$/Mpc). Moreover, our model leads to inferred bias and cosmological parameters compatible within 1$σ$ with their reference values. We anticipate that our method will be a promising candidate for analysing forthcoming Stage-IV survey data.

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Characterizing Structure Formation through Instance Segmentation

Dark matter haloes form from small perturbations to the almost homogeneous density field of the early universe. Although it is known how large these initial perturbations must be to form haloes, it is rather poorly understood how to predict which particles will end up belonging to which halo. However, it is this process that determines the Lagrangian shape of protohaloes and is therefore essential to understand their mass, spin and formation history. Here, we present a machine-learning framework to learn how the protohalo regions of different haloes emerge from the initial density field. This involves one neural network to distinguish semantically which particles become part of any halo and a second neural network that groups these particles by halo membership into different instances. This instance segmentation is done through the Weinberger method, in which the network maps particles into a pseudo-space representation where different instances can be distinguished easily through a simple clustering algorithm. Our model reliably predicts the masses and Lagrangian shapes of haloes object-by-object, as well as summary statistics like the halo-mass function. We find that our model extracts information close to optimal by comparing it to the degree of agreement between two N-body simulations with slight differences in their initial conditions. We publish our model open-source and suggest that it can be used to inform analytical methods of structure formation by studying the effect of systematic manipulations of the initial conditions.

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The cosmology dependence of the concentration-mass-redshift relation

The concentrations of dark matter haloes provide crucial information about their internal structure and how it depends on mass and redshift -- the so-called concentration-mass-redshift relation, denoted $c(M,z)$. We present here an extensive study of the cosmology-dependence of $c(M,z)$ that is based on a suite of 72 gravity-only, full N-body simulations in which the following cosmological parameters were varied: $σ_{8}$, $Ω_{\mathrm{M}}$, $Ω_{\mathrm{b}}$, $n_{\mathrm{s}}$, $h$, $M_ν$, $w_{0}$ and $w_{\mathrm{a}}$. We characterize the impact of these parameters on concentrations for different halo masses and redshifts. In agreement with previous works, and for all cosmologies studied, we find that there exists a tight correlation between the characteristic densities of dark matter haloes within their scale radii, $r_{-2}$, and the critical density of the Universe at a suitably defined formation time. This finding, when combined with excursion set modelling of halo formation histories, allows us to accurately predict the concentrations of dark matter haloes as a function of mass, redshift, and cosmology. We use our simulations to test the reliability of a number of published models for predicting halo concentration and highlight when they succeed or fail to reproduce the cosmological $c(M,z)$ relation.

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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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Tomographic Constraints on Gravity from Angular Redshift Fluctuations in the Late Universe

Fluctuations in sky maps of the galaxy redshifts, dubbed as angular redshift fluctuations (ARF), contain precise information about the growth rate of structures and the nature of gravity in the Universe. Specifically, ARF constrain the combination of cosmological parameters $H/H_0\,fσ_8(z)$, while being an intrinsically tomographic probe and largely insensitive to many observational systematic errors, all this without requiring the assumption of any redshift-to-distance relation under a given fiducial cosmology. We present the first cosmological constraints derived from ARF by using BOSS LOWZ+CMASS DR12 galaxy samples, obtaining 7\%-accurate constraints on $H/H_0 fσ_8(z)$ at more than 20 redshifts over the range $z \in [0.26,0.72]$. Our best-fitting value is $10\%$ larger, but compatible at the $1.4σ$ level, than the $Λ$CDM expectation set by {\it Planck} observations of the Cosmic Microwave Background (CMB) radiation. Our tomographic measurements, combined with these CMB data, provides one of the strongest constraints on the gravity index $γ$, $γ=0.44^{+0.09}_{-0.07}$, which lies within $2σ$ from the prediction of General Relativity ($γ_{\rm GR}\simeq 0.55$).

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High resolution tomography for galaxy spectroscopic surveys with angular redshift fluctuations

In the context of next-generation spectroscopic galaxy surveys, new statistics of the distribution of matter are currently being developed. Among these, we investigated the angular redshift fluctuations (ARF), which probe the information contained in the projected redshift distribution of galaxies. Relying on the Fisher formalism, we show how ARF will provide complementary cosmological information compared to traditional angular galaxy clustering. We tested both the standard $\mathrm{ΛCDM}$ model and the $\mathrm{wCDM}$ extension. We find that the cosmological and galaxy bias parameters express different degeneracies when inferred from ARF or from angular galaxy clustering. As such, combining both observables breaks these degeneracies and greatly decreases the marginalised uncertainties by a factor of at least two on most parameters for the $\mathrm{ΛCDM}$ and $\mathrm{wCDM}$ models. We find that the ARF combined with angular galaxy clustering provide a great way to probe dark energy by increasing the figure of merit of the $w_0$-$w_{\rm a}$ parameter set by a factor of more than ten compared to angular galaxy clustering alone. Finally, we compared ARF to the CMB lensing constraints on the galaxy bias parameters. We show that a joint analysis of ARF and angular galaxy clustering improves constraints by $\sim 40\%$ on galaxy bias compared to a joint analysis of angular galaxy clustering and CMB lensing.

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Joint galaxy-galaxy lensing and clustering constraints on galaxy formation

We compare predictions for galaxy-galaxy lensing profiles and clustering from the Henriques et al. (2015) public version of the Munich semi-analytical model of galaxy formation (SAM) and the IllustrisTNG suite, primarily TNG300, with observations from KiDS+GAMA and SDSS-DR7 using four different selection functions for the lenses (stellar mass, stellar mass and group membership, stellar mass and isolation criteria, stellar mass and colour). We find that this version of the SAM does not agree well with the current data for stellar mass-only lenses with $M_\ast > 10^{11}\,M_\odot$. By decreasing the merger time for satellite galaxies as well as reducing the radio-mode AGN accretion efficiency in the SAM, we obtain better agreement, both for the lensing and the clustering, at the high mass end. We show that the new model is consistent with the signals for central galaxies presented in Velliscig et al. (2017). Turning to the hydrodynamical simulation, TNG300 produces good lensing predictions, both for stellar mass-only ($χ^2 = 1.81$ compared to $χ^2 = 7.79$ for the SAM), and locally brightest galaxies samples ($χ^2 = 3.80$ compared to $χ^2 = 5.01$). With added dust corrections to the colours it matches the SDSS clustering signal well for red low mass galaxies. We find that both the SAMs and TNG300 predict $\sim 50\,\%$ excessive lensing signals for intermediate mass red galaxies with $10.2 < \log_{10} M_\ast [ M_\odot ] < 11.2$ at $r \approx 0.6\,h^{-1}\,\mathrm{Mpc}$, which require further theoretical development.

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Redshift-space effects in voids and their impact on cosmological tests. Part I: the void size function

Voids are promising cosmological probes. Nevertheless, every cosmological test based on voids must necessarily employ methods to identify them in redshift space. Therefore, redshift-space distortions (RSD) and the Alcock-Paczynski effect (AP) have an impact on the void identification process itself generating distortion patterns in observations. Using a spherical void finder, we developed a statistical and theoretical framework to describe physically the connection between the identification in real and redshift space. We found that redshift-space voids above the shot noise level have a unique real-space counterpart spanning the same region of space, they are systematically bigger and their centres are preferentially shifted along the line of sight. The expansion effect is a by-product of RSD induced by tracer dynamics at scales around the void radius, whereas the off-centring effect constitutes a different class of RSD induced at larger scales by the global dynamics of the whole region containing the void. The volume of voids is also altered by the fiducial cosmology assumed to measure distances, this is the AP change of volume. These three systematics have an impact on cosmological statistics. In this work, we focus on the void size function. We developed a theoretical framework to model these effects and tested it with a numerical simulation, recovering the statistical properties of the abundance of voids in real space. This description depends strongly on cosmology. Hence, we lay the foundations for improvements in current models of the abundance of voids in order to obtain unbiased cosmological constraints from redshift surveys.

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How to add massive neutrinos to your $Λ$CDM simulation -- extending cosmology rescaling algorithms

Providing accurate predictions for the spatial distribution of matter and luminous tracers in the presence of massive neutrinos is an important task, given the imminent arrival of highly accurate large-scale structure observations. In this work, we address this challenge by extending cosmology-rescaling algorithms to massive neutrino cosmologies. In this way, a $Λ$CDM simulation can be modified to provide nonlinear structure formation predictions in the presence a hot component of arbitrary mass, and, if desired, to include non-gravitational modifications to the clustering of matter on large scales. We test the accuracy of the method by comparing its predictions to a suite of simulations carried out explicitly including a neutrino component in its evolution equations. We find that, for neutrino masses in the range $M_ν\in [0.06, 0.3] ~ \mathrm{eV}$ the matter power spectrum is recovered to better than $1\%$ on all scales $k<2~h~\mathrm{Mpc}^{-1}$. Similarly, the halo mass function is predicted at a few percent level over the range $M_{\rm halo} \in [10^{12}, 10^{15}] ~ h^{-1} ~ \mathrm{M}_{\odot}$, and so do also the multipoles of the galaxy 2-point correlation function in redshift space over $r \in [0.1, 200] ~ h^{-1} ~ \mathrm{Mpc}$. We provide parametric forms for the necessary transformations, as a function of $Ω_{\rm m}$ and $Ω_ν$ for various target redshifts.

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One simulation to have them all: performance of the Bias Assignment Method against N-body simulations

In this paper we demonstrate that the information encoded in \emph{one} single (sufficiently large) $N$-body simulation can be used to reproduce arbitrary numbers of halo catalogues, using approximated realisations of dark matter density fields with different initial conditions. To this end we use as a reference one realisation (from an ensemble of $300$) of the Minerva $N$-body simulations and the recently published Bias Assignment Method to extract the local and non-local bias linking the halo to the dark matter distribution. We use an approximate (and fast) gravity solver to generate $300$ dark matter density fields from the down-sampled initial conditions of the reference simulation and sample each of these fields using the halo-bias and a kernel, both calibrated from the arbitrarily chosen realisation of the reference simulation. We show that the power spectrum, its variance and the three-point statistics are reproduced within $\sim 2\%$ (up to $k\sim1.0\,h\,{\rm Mpc}^{-1}$), $\sim 5-10\%$ and $\sim 10\%$, respectively. Using a model for the real space power spectrum (with three free bias parameters), we show that the covariance matrices obtained from our procedure lead to parameter uncertainties that are compatible within $\sim 10\%$ with respect to those derived from the reference covariance matrix, and motivate approaches that can help to reduce these differences to $\sim 1\%$. Our method has the potential to learn from one simulation with moderate volumes and high-mass resolution and extrapolate the information of the bias and the kernel to larger volumes, making it ideal for the construction of mock catalogues for present and forthcoming observational campaigns such as Euclid or DESI.

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The bias of dark matter tracers: assessing the accuracy of mapping techniques

We present a comparison between approximated methods for the construction of mock catalogs based on the halo-bias mapping technique. To this end, we use as reference a high resolution $N$-body simulation of 3840$^3$ dark matter particles on a 400$h^{-1}\rm{Mpc}$ cube box from the Multidark suite. In particular, we explore parametric versus non-parametric bias mapping approaches and compare them at reproducing the halo distribution in terms of the two and three point statistics down to $\sim 10^8\,{\rm M}_{\odot}\,h^{-1}$ halo masses. Our findings demonstrate that the parametric approach remains inaccurate even including complex deterministic and stochastic components. On the contrary, the non-parametric one is indistinguishable from the reference $N$-body calculation in the power-spectrum beyond $k=1\,h\,{\rm Mpc}^{-1}$, and in the bispectrum for typical configurations relevant to baryon acoustic oscillation analysis. We conclude, that approaches which extract the full bias information from $N$-body simulations in a non-parametric fashion are ready for the analysis of the new generation of large scale structure surveys.

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Non-fiducial cosmological test from geometrical and dynamical distortions around voids

We present a new cosmological test using the distribution of galaxies around cosmic voids without assuming a fiducial cosmology. The test is based on a physical model for the void-galaxy cross-correlation function projected along and perpendicular to the line of sight. We treat correlations in terms of void-centric angular distances and redshift differences between void-galaxy pairs, hence it is not necessary to assume a fiducial cosmology. This model reproduces the coupled dynamical (Kaiser effect, RSD) and geometrical (Alcock-Paczynski effect, GD) distortions that affect the correlation measurements. It also takes into account the scale mixing due to the projection ranges in both directions. The model is general, so it can be applied to an arbitrary cylindrical binning scheme, not only in the case of the projected correlations. It primarily depends on two cosmological parameters: $Ω_m$, the matter fraction of the Universe today (sensitive to GD), and $β$, the ratio between the growth rate factor of density perturbations and the tracer bias (sensitive to RSD). In the context of the new generation of galaxy spectroscopic surveys, we calibrated the test using the Millennium XXL simulation for different redshifts. The method successfully recovers the cosmological parameters. We studied the effect of measuring with different projection ranges, finding robust results up to wide ranges. The resulting data covariance matrices are relatively small, which reduces the noise in the Gaussian likelihood analysis and will allow the usage of a smaller number of mock catalogues. The performance evaluated in this work indicates that the developed method is a promising test to be applied on real data.

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Halo mass and weak galaxy-galaxy lensing profiles in rescaled cosmological $N$-body simulations

We investigate 3D density and weak lensing profiles of dark matter haloes predicted by a cosmology-rescaling algorithm for $N$-body simulations. We extend the rescaling method of Angulo & White (2010) and Angulo & Hilbert (2015) to improve its performance on intra-halo scales by using models for the concentration-mass-redshift relation based on excursion set theory. The accuracy of the method is tested with numerical simulations carried out with different cosmological parameters. We find that predictions for median density profiles are more accurate than $\sim 5\,\%$ for haloes with masses of $10^{12.0} - 10^{14.5} h^{-1}\,M_{\odot}$ for radii $0.05 < r/r_{200\text{m}} < 0.5$, and for cosmologies with $Ω_\text{m} \in [0.15,\,0.40]$ and $σ_8 \in [0.6,\,1.0]$. For larger radii, $0.5 < r/r_{200\text{m}} < 5$, the accuracy degrades to $\sim20\,\%$, due to inaccurate modelling of the cosmological and redshift dependence of the splashback radius. For changes in cosmology allowed by current data, the residuals decrease to $\lesssim2\,\%$ up to scales twice the virial radius. We illustrate the usefulness of the method by estimating the mean halo mass of a mock galaxy group sample. We find that the algorithm's accuracy is sufficient for current data. Improvements in the algorithm, particularly in the modelling of baryons, are likely required for interpreting future (dark energy task force stage IV) experiments.

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The effect of photometric redshift uncertainties on galaxy clustering and baryonic acoustic oscillations

In the upcoming era of high-precision galaxy surveys, it becomes necessary to understand the impact of redshift uncertainties on cosmological observables. In this paper we explore the effect of sub-percent photometric redshift errors (photo-$z$ errors) on galaxy clustering and baryonic acoustic oscillations (BAO). Using analytic expressions and results from $1\,000$ $N$-body simulations, we show how photo-$z$ errors modify the amplitude of moments of the 2D power spectrum, their variances, the amplitude of BAO, and the cosmological information in them. We find that: a) photo-$z$ errors suppress the clustering on small scales, increasing the relative importance of shot noise, and thus reducing the interval of scales available for BAO analyses; b) photo-$z$ errors decrease the smearing of BAO due to non-linear redshift-space distortions (RSD) by giving less weight to line-of-sight modes; and c) photo-$z$ errors (and small-scale RSD) induce a scale dependence on the information encoded in the BAO scale, and that reduces the constraining power on the Hubble parameter. Using these findings, we propose a template that extracts unbiased cosmological information from samples with photo-$z$ errors with respect to cases without them. Finally, we provide analytic expressions to forecast the precision in measuring the BAO scale, showing that spectro-photometric surveys will measure the expansion history of the Universe with a precision competitive to that of spectroscopic surveys.

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The Mass-Concentration-Redshift Relation of Cold and Warm Dark Matter Halos

We use a suite of cosmological simulations to study the mass-concentration-redshift relation, $c({\rm M},z)$, of dark matter halos. Our simulations include standard $Λ$-cold dark matter (CDM) models, and additional runs with truncated power spectra, consistent with a thermal warm dark matter (WDM) scenario. We find that the mass profiles of CDM and WDM halos are self-similar and well approximated by the Einasto profile. The $c({\rm M},z)$ relation of CDM halos is monotonic: concentrations decrease with increasing virial mass at fixed redshift, and decrease with increasing redshift at fixed mass. The mass accretion histories (MAHs) of CDM halos are also scale-free, and can be used to infer concentrations directly. These results do not apply to WDM halos: their MAHs are not scale-free because of the characteristic scale imposed by the power-spectrum suppression. Further, the WDM $c({\rm M},z)$ relation is non-monotonic: concentrations peak at a mass scale dictated by the truncation scale, and decrease at higher and lower masses. We show that the assembly history of a halo can still be used to infer its concentration, provided that the total mass of its progenitors is considered (the "collapsed mass history"; CMH), rather than just that of its main ancestor. This exploits the scale-free nature of CMHs to derive a simple scaling that reproduces the mass-concentration-redshift relation of both CDM and WDM halos over a vast range of halo masses and redshifts. Our model therefore provides a robust account of the mass, redshift, cosmology and power spectrum dependence of dark matter halo concentrations.

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