arXiv subjects

Carlo Giocoli

Publications and source records attributed to Carlo Giocoli.

At least 55 records · Page 3Linked to original sources

arXiv2020

Testing the Reliability of Fast Methods for Weak Lensing Simulations: WL-MOKA on PINOCCHIO

The generation of simulated convergence maps is of key importance in fully exploiting weak lensing by Large Scale Structure (LSS) from which cosmological parameters can be derived. In this paper we present an extension of the PINOCCHIO code which produces catalogues of dark matter haloes so that it is capable of simulating weak lensing by LSS. Like WL-MOKA, the method starts with a random realisation of cosmological initial conditions, creates a halo catalogue and projects it onto the past-light-cone, and paints in haloes assuming parametric models for the mass density distribution within them. Large scale modes that are not accounted for by the haloes are constructed using linear theory. We discuss the systematic errors affecting the convergence power spectra when Lagrangian Perturbation Theory at increasing order is used to displace the haloes within PINOCCHIO, and how they depend on the grid resolution. Our approximate method is shown to be very fast when compared to full ray-tracing simulations from an N-Body run and able to recover the weak lensing signal, at different redshifts, with a few percent accuracy. It also allows for quickly constructing weak lensing covariance matrices, complementing PINOCCHIO's ability of generating the cluster mass function and galaxy clustering covariances and thus paving the way for calculating cross covariances between the different probes. This work advances these approximate methods as tools for simulating and analysing surveys data for cosmological purposes.

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arXiv2020

The stellar-to-halo mass relation over the past 12 Gyr

Understanding how galaxy properties are linked to the dark matter halos they reside in, and how they co-evolve is a powerful tool to constrain the processes related to galaxy formation. The stellar-to-halo mass relation (SHMR) and its evolution over the history of the Universe provides insights on galaxy formation models and allows to assign galaxy masses to halos in N-body dark matter simulations. We use a statistical approach to link the observed galaxy stellar mass functions on the COSMOS field to dark matter halo mass functions from the DUSTGRAIN simulation and from a theoretical parametrization from z=0 to z=4. We also propose an empirical model to describe the evolution of the stellar-to-halo mass relation as a function of redshift. We calculate the star-formation efficiency (SFE) of galaxies and compare results with previous works and semi-analytical models.

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arXiv2019

Clustering and redshift-space distortions in modified gravity models with massive neutrinos

Modified gravity and massive neutrino cosmologies are two of the most interesting scenarios that have been recently explored to account for possible observational deviations from the concordance $Λ$-cold dark matter ($Λ$CDM) model. In this context, we investigated the large-scale structure of the Universe by exploiting the \dustp simulations that implement, simultaneously, the effects of $f(R)$ gravity and massive neutrinos. To study the possibility of breaking the degeneracy between these two effects, we analysed the redshift-space distortions in the clustering of dark matter haloes at different redshifts. Specifically, we focused on the monopole and quadrupole of the two-point correlation function, both in real and redshift space. The deviations with respect to $Λ$CDM model have been quantified in terms of the linear growth rate parameter. We found that redshift-space distortions provide a powerful probe to discriminate between $Λ$CDM and modified gravity models, especially at high redshifts ($z \gtrsim 1$), even in the presence of massive neutrinos.

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arXiv2019

Distinguishing standard and modified gravity cosmologies with machine learning

We present a convolutional neural network to classify distinct cosmological scenarios based on the statistically similar weak-lensing maps they generate. Modified gravity (MG) models that include massive neutrinos can mimic the standard concordance model ($Λ$CDM) in terms of Gaussian weak-lensing observables. An inability to distinguish viable models that are based on different physics potentially limits a deeper understanding of the fundamental nature of cosmic acceleration. For a fixed redshift of sources, we demonstrate that a machine learning network trained on simulated convergence maps can discriminate between such models better than conventional higher-order statistics. Results improve further when multiple source redshifts are combined. To accelerate training, we implement a novel data compression strategy that incorporates our prior knowledge of the morphology of typical convergence map features. Our method fully distinguishes $Λ$CDM from its most similar MG model on noise-free data, and it correctly identifies among the MG models with at least 80% accuracy when using the full redshift information. Adding noise lowers the correct classification rate of all models, but the neural network still significantly outperforms the peak statistics used in a previous analysis.

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arXiv2019

Dark matter stripping in galaxy clusters: a look at the Stellar to Halo Mass relation in the Illustris simulation

Satellite galaxies in galaxy clusters represent a significant fraction of the global galaxy population. Because of the unusual dense environment of clusters, their evolution is driven by different mechanisms than the ones affecting field or central galaxies. Understanding the different interactions they are subject to, and how they are influenced by them, is therefore an important step towards explaining the global picture of galaxy evolution. In this paper, we use the publicly-available high resolution hydrodynamical simulation Illustris-1 to study satellite galaxies in the three most massive host haloes (with masses $M_{200} > 10^{14}\,h^{-1}\rm{M}_{\odot}$) at $z=0$. We measure the Stellar-to-Halo Mass Relation (hereafter SHMR) of the galaxies, and find that for satellites it is shifted towards lower halo masses compared to the SHMR of central galaxies. We provide simple fitting functions for both the central and satellite SHMR. To explain the shift between the two, we follow the satellite galaxies since their time of accretion into the clusters, and quantify the impact of dark matter stripping and star formation. We find that subhaloes start losing their dark matter as soon as they get closer than $\sim 1.5\times R_{\rm{vir}}$ to the centre of their host, and that up to 80\% of their dark matter content gets stripped during infall. On the other hand, star formation quenching appears to be delayed, and galaxies continue to form stars for a few Gyr after accretion. The combination of these two effects impacts the ratio of stellar to dark matter mass which varies drastically during infall, from 0.03 to 0.3.

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arXiv2019

UNIT project: Universe $N$-body simulations for the Investigation of Theoretical models from galaxy surveys

We present the UNIT $N$-body cosmological simulations project, designed to provide precise predictions for nonlinear statistics of the galaxy distribution. We focus on characterizing statistics relevant to emission line and luminous red galaxies in the current and upcoming generation of galaxy surveys. We use a suite of precise particle mesh simulations (FastPM) as well as with full $N$-body calculations with a mass resolution of $\sim 1.2\times10^9\,h^{-1}$M$_{\odot}$ to investigate the recently suggested technique of Angulo & Pontzen 2016 to suppress the variance of cosmological simulations We study redshift space distortions, cosmic voids, higher order statistics from $z=2$ down to $z=0$. We find that both two- and three-point statistics are unbiased. Over the scales of interest for baryon acoustic oscillations and redshift-space distortions, we find that the variance is greatly reduced in the two-point statistics and in the cross correlation between halos and cosmic voids, but is not reduced significantly for the three-point statistics. We demonstrate that the accuracy of the two-point correlation function for a galaxy survey with effective volume of 20 ($h^{-1}$Gpc)$^3$ is improved by about a factor of 40, indicating that two pairs of simulations with a volume of 1 ($h^{-1}$Gpc)$^3$ lead to the equivalent variance of $\sim$150 such simulations. The $N$-body simulations presented here thus provide an effective survey volume of about seven times the effective survey volume of DESI or Euclid. The data from this project, including dark matter fields, halo catalogues, and their clustering statistics, are publicly available at http://www.unitsims.org.

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arXiv2019

On the dissection of degenerate cosmologies with machine learning

Based on the DUSTGRAIN-pathfinder suite of simulations, we investigate observational degeneracies between nine models of modified gravity and massive neutrinos. Three types of machine learning techniques are tested for their ability to discriminate lensing convergence maps by extracting dimensional reduced representations of the data. Classical map descriptors such as the power spectrum, peak counts and Minkowski functionals are combined into a joint feature vector and compared to the descriptors and statistics that are common to the field of digital image processing. To learn new features directly from the data we use a Convolutional Neural Network (CNN). For the mapping between feature vectors and the predictions of their underlying model, we implement two different classifiers; one based on a nearest-neighbour search and one that is based on a fully connected neural network. We find that the neural network provides a much more robust classification than the nearest-neighbour approach and that the CNN provides the most discriminating representation of the data. It achieves the cleanest separation between the different models and the highest classification success rate of 59% for a single source redshift. Once we perform a tomographic CNN analysis, the total classification accuracy increases significantly to 76% with no observational degeneracies remaining. Visualising the filter responses of the CNN at different network depths provides us with the unique opportunity to learn from very complex models and to understand better why they perform so well.

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arXiv2018

Breaking degeneracies in modified gravity with higher (than 2nd) order weak-lensing statistics

General relativity (GR) has been well tested up to solar system scales, but it is much less certain that standard gravity remains an accurate description on the largest, that is, cosmological, scales. Many extensions to GR have been studied that are not yet ruled out by the data, including by that of the recent direct gravitational wave detections. Degeneracies among the standard model ($Λ$CDM) and modified gravity (MG) models, as well as among different MG parameters, must be addressed in order to best exploit information from current and future surveys and to unveil the nature of dark energy. We propose various higher-order statistics in the weak-lensing signal as a new set of observables able to break degeneracies between massive neutrinos and MG parameters. We have tested our methodology on so-called $f(R)$ models, which constitute a class of viable models that can explain the accelerated universal expansion by a modification of the fundamental gravitational interaction. We have explored a range of these models that still fit current observations at the background and linear level, and we show using numerical simulations that certain models which include massive neutrinos are able to mimic $Λ$CDM in terms of the 3D power spectrum of matter density fluctuations. We find that depending on the redshift and angular scale of observation, non-Gaussian information accessed by higher-order weak-lensing statistics can be used to break the degeneracy between $f(R)$ models and $Λ$CDM. In particular, peak counts computed in aperture mass maps outperform third- and fourth-order moments.

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arXiv2018

Weak Lensing Light-Cones in Modified Gravity simulations with and without Massive Neutrinos

We present a novel suite of cosmological N-body simulations called the DUSTGRAIN-pathfinder, implementing simultaneously the effects of an extension to General Relativity in the form of $f(R)$ gravity and of a non-negligible fraction of massive neutrinos. We describe the generation of simulated weak lensing and cluster counts observables within a past light-cone extracted from these simulations. The simulations have been performed by means of a combination of the MG-GADGET code and a particle-based implementation of massive neutrinos, while the light-cones have been generated using the MapSim pipeline allowing us to compute weak lensing maps through a ray-tracing algorithm for different values of the source plane redshift. The mock observables extracted from our simulations will be employed for a series of papers focussed on understanding and possibly breaking the well-known observational degeneracy between $f(R)$ gravity and massive neutrinos, i.e. the fact that some specific combinations of the characteristic parameters for these two phenomena (the $f_{R0}$ scalar amplitude and the total neutrino mass $Σm_ν$) may result indistinguishable from the standard $\mathrm{ΛCDM}$ cosmology through several standard observational probes. In particular, in the present work we show how a tomographic approach to weak lensing statistics could allow - especially for the next generation of wide-field surveys - to disentangle some of the models that appear statistically indistinguishable through standard single-redshift weak lensing probe.

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arXiv2018

Gravitational lensing detection of an extremely dense environment around a galaxy cluster

Galaxy clusters form at the highest density nodes of the cosmic web. The clustering of massive halos is enhanced relative to the general mass distribution and matter beyond the virial region is strongly correlated to the halo mass (halo bias). Clustering can be further enhanced depending on halo properties other than mass (secondary bias). The questions of how much and why the regions surrounding rich clusters are over-dense are still unanswered. Here, we report the analysis of the environment bias in a sample of very massive clusters, selected through the Sunyaev-Zel'dovich effect by the Planck mission. We present the first detection of the correlated dark matter associated to a single cluster, PSZ2 G099.86+58.45. The system is extremely rare in the current paradigm of structure formation. The gravitational lensing signal was traced up to 30 megaparsecs with high signal-to-noise ratio ~3.4. The measured shear is very large and points at environment matter density in notable excess of the cosmological mean. The boosting of the correlated dark matter density around high mass halos can be very effective. Together with ensemble studies of the large scale structure, lensing surveys can picture the surroundings of single haloes.

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arXiv2018

The effect of baryons in the cosmological lensing PDFs

Observational cosmology is passing through a unique moment of grandeur with the amount of quality data growing fast. However, in order to better take advantage of this moment, data analysis tools have to keep up the pace. Understanding the effect of baryonic matter on the large-scale structure is one of the challenges to be faced in cosmology. In this work, we have thoroughly studied the effect of baryonic physics on different lensing statistics. Making use of the Magneticum Pathfinder suite of simulations we show that the influence of luminous matter on the 1-point lensing statistics of point sources is significant, enhancing the probability of magnified objects with $μ>3$ by a factor of $2$ and the occurrence of multiple-images by a factor $5-500$ depending on the source redshift and size. We also discuss the dependence of the lensing statistics on the angular resolution of sources. Our results and methodology were carefully tested in order to guarantee that our uncertainties are much smaller than the effects here presented.

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arXiv2018

Weak Lensing Peaks in Simulated Light-Cones: Investigating the Coupling between Dark Matter and Dark Energy

In this paper, we study the statistical properties of weak lensing peaks in light-cones generated from cosmological simulations. In order to assess the prospects of such observable as a cosmological probe, we consider simulations that include interacting Dark Energy (hereafter DE) models with coupling term between DE and Dark Matter. Cosmological models that produce a larger population of massive clusters have more numerous high signal-to-noise peaks; among models with comparable numbers of clusters those with more concentrated haloes produce more peaks. The most extreme model under investigation shows a difference in peak counts of about $20\%$ with respect to the reference $\mathrmΛ$CDM model. We find that peak statistics can be used to distinguish a coupling DE model from a reference one with the same power spectrum normalisation. The differences in the expansion history and the growth rate of structure formation are reflected in their halo counts, non-linear scale features and, through them, in the properties of the lensing peaks. For a source redshift distribution consistent with the expectations of future space-based wide field surveys, we find that typically seventy percent of the cluster population contributes to weak-lensing peaks with signal-to-noise ratios larger than two, and that the fraction of clusters in peaks approaches one-hundred percent for haloes with redshift z$\leq$0.5. Our analysis demonstrates that peak statistics are an important tool for disentangling DE models by accurately tracing the structure formation processes as a function of the cosmic time.

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arXiv2018

Accretion of satellites onto central galaxies in clusters: merger mass ratios and orbital parameters

We study the statistical properties of mergers between central and satellite galaxies in galaxy clusters in the redshift range $0<z<1$, using a sample of dark-matter only cosmological N-body simulations from Le SBARBINE dataset. Using a spherical overdensity algorithm to identify dark-matter haloes, we construct halo merger trees for different values of the over-density $Δ_c$. While the virial overdensity definition allows us to probe the accretion of satellites at the cluster virial radius $r_{vir}$, higher overdensities probe satellite mergers in the central region of the cluster, down to $\approx 0.06 r_{vir}$, which can be considered a proxy for the accretion of satellite galaxies onto central galaxies. We find that the characteristic merger mass ratio increases for increasing values of $Δ_c$: more than $60\%$ of the mass accreted by central galaxies since $z\approx 1$ comes from major mergers. The orbits of satellites accreting onto central galaxies tend to be more tangential and more bound than orbits of haloes accreting at the virial radius. The obtained distributions of merger mass ratios and orbital parameters are useful to model the evolution of the high-mass end of the galaxy scaling relations without resorting to hydrodynamic cosmological simulations.

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arXiv2018

Modelling the line-of-sight contribution in substructure lensing

We investigate how Einstein rings and magnified arcs are affected by small-mass dark-matter haloes placed along the line-of-sight to gravitational lens systems. By comparing the gravitational signature of line-of-sight haloes with that of substructures within the lensing galaxy, we derive a mass-redshift relation that allows us to rescale the detection threshold (i.e. lowest detectable mass) for substructures to a detection threshold for line-of-sight haloes at any redshift. We then quantify the line-of-sight contribution to the total number density of low-mass objects that can be detected through strong gravitational lensing. Finally, we assess the degeneracy between substructures and line-of-sight haloes of different mass and redshift to provide a statistical interpretation of current and future detections, with the aim of distinguishing between CDM and WDM. We find that line-of-sight haloes statistically dominate with respect to substructures, by an amount that strongly depends on the source and lens redshifts, and on the chosen dark matter model. Substructures represent about 30 percent of the total number of perturbers for low lens and source redshifts (as for the SLACS lenses), but less than 10 per cent for high redshift systems. We also find that for data with high enough signal-to-noise ratio and angular resolution, the non-linear effects arising from a double-lens-plane configuration are such that one is able to observationally recover the line-of-sight halo redshift with an absolute error precision of 0.15 at the 68 per cent confidence level.

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arXiv2017

Stellar-to-halo mass relation of cluster galaxies

In the hierarchical formation model, galaxy clusters grow by accretion of smaller groups or isolated galaxies. During the infall into the centre of a cluster, the properties of accreted galaxies change. In particular, both observations and numerical simulations suggest that its dark matter halo is stripped by the tidal forces of the host. We use galaxy-galaxy weak lensing to measure the average mass of dark matter haloes of satellite galaxies as a function of projected distance to the centre of the host, for different stellar mass bins. Assuming that the stellar component of the galaxy is less disrupted by tidal stripping, stellar mass can be used as a proxy of the infall mass. We study the stellar to halo mass relation of satellites as a function of the cluster-centric distance to measure tidal stripping. We use the shear catalogues of the DES science verification archive, the CFHTLenS and the CFHT Stripe 82 (CS82) surveys, and we select satellites from the redMaPPer catalogue of clusters. For galaxies located in the outskirts of clusters, we find a stellar to halo mass relation in good agreement with the theoretical expectations from \citet{moster2013} for central galaxies. In the centre of the cluster, we find that this relation is shifted to smaller halo mass for a given stellar mass. We interpret this finding as further evidence for tidal stripping of dark matter haloes in high density environments.

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arXiv2017

Hubble Frontier Fields: systematic errors in strong lensing models of galaxy clusters - Implications for cosmography

Strong gravitational lensing by galaxy clusters is a fundamental tool to study dark matter and constrain the geometry of the Universe. Recently, the Hubble Space Telescope Frontier Fields programme has allowed a significant improvement of mass and magnification measurements but lensing models still have a residual root mean square between 0.2 arcsec and few arcsec- onds, not yet completely understood. Systematic errors have to be better understood and treated in order to use strong lensing clusters as reliable cosmological probes. We have analysed two simulated Hubble-Frontier-Fields-like clusters from the Hubble Frontier Fields Comparison Challenge, Ares and Hera. We use several estimators (relative bias on magnification, den- sity profiles, ellipticity and orientation) to quantify the goodness of our reconstructions by comparing our multiple models, optimized with the parametric software LENSTOOL , with the input models. We have quantified the impact of systematic errors arising, first, from the choice of different density profiles and configurations and, secondly, from the availability of con- straints (spectroscopic or photometric redshifts, redshift ranges of the background sources) in the parametric modelling of strong lensing galaxy clusters and therefore on the retrieval of cosmological parameters. We find that substructures in the outskirts have a significant im- pact on the position of the multiple images, yielding tighter cosmological contours. The need for wide-field imaging around massive clusters is thus reinforced. We show that competitive cosmological constraints can be obtained also with complex multimodal clusters and that photometric redshifts improve the constraints on cosmological parameters when considering a narrow range of (spectroscopic) redshifts for the sources.

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arXiv2017

Fast Weak Lensing Simulations with Halo Model

Full ray-tracing maps of gravitational lensing, constructed from N-Body simulations, represent a fundamental tool to interpret present and future weak lensing data. However the limitation of computational resources and storage capabilities severely restrict the number of realizations that can be performed in order to accurately sample both the cosmic shear models and covariance matrices. In this paper we present a halo model formalism for weak gravitational lensing that alleviates these issues by producing weak-lensing mocks at a reduced computational cost. Our model takes as input the halo population within a desired light-cone and the linear power spectrum of the underlined cosmological model. We examine the contribution given by the presence of substructures within haloes to the cosmic shear power spectrum and quantify it to the percent level. Our method allows us to reconstruct high-resolution convergence maps, for any desired source redshifts, of light-cones that realistically trace the matter density distribution in the universe, account for masked area and sample selections. We compare our analysis on the same large scale structures constructed using ray-tracing techniques and find very good agreements both in the linear and non-linear regimes up to few percent levels. The accuracy and speed of our method demonstrate the potential of our halo model for weak lensing statistics and the possibility to generate a large sample of convergence maps for different cosmological models as needed for the analysis of large galaxy redshift surveys.

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arXiv2016

A look to the inside of haloes: a characterisation of the halo shape as a function of overdensity in the Planck cosmology

In this paper we study the triaxial properties of dark matter haloes of a wide range of masses extracted from a set of cosmological N-body simulations. We measure the shape at different distances from the halo centre (characterised by different overdensity thresholds), both in three and in two dimensions. We discuss how halo triaxiality increases with mass, redshift and distance from the halo centre. We also examine how the orientation of the different ellipsoids are aligned with each other and what is the gradient in internal shapes for halos with different virial configurations. Our findings highlight that the internal part of the halo retains memory of the violent formation process keeping the major axis oriented toward the preferential direction of the in-falling material while the outer part becomes rounder due to continuous isotropic merging events. This effect is clearly evident in high mass haloes - which formed more recently - while it is more blurred in low mass haloes. We present simple distributions that may be used as priors for various mass reconstruction algorithms, operating in different wavelengths, in order to recover a more complex and realistic dark matter distribution of isolated and relaxed systems.

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