The cosmic web connection to the dark matter halo distribution through gravity

In this letter we investigate the connection between the cosmic web and the halo distribution through the gravitational potential. We combine three fields of research, cosmic web classification, perturbation theory expansions of the halo bias, and halo (galaxy) mock catalog making methods. In particular, we use the invariants of the tidal field tensor as generating functions (dubbed I-web), to reproduce the halo number counts of a reference catalog from full gravity calculations, populating the dark matter field on a mesh well into the non-linear regime ($\sim5$ Mpc scales). Our results show an unprecedented agreement with the reference power spectrum within 0.5% up to $k=0.72\,h$ Mpc$^{-1}$. By analysing the three point statistics on large scales (configurations of up to $k=0.2\,h$ Mpc$^{-1}$), we find evidence for non-local bias at the 4.8 $\sigma$ confidence level (an information gain of $\sim$ 3.4 $\sigma$ over the commonly used T-web), being fully compatible with the reference catalog. In particular, we find that a detailed description of tidal anisotropic clustering on large scales is crucial to achieve this accuracy. We conclude that the I-web can potentially be useful to study the cosmic web, to improve the generation of mock galaxy catalogs, to improve on halo mass reconstructions, to study primordial non-Gaussianities, to develop new effective Eulerian galaxy bias models at the field level, and to investigate galaxy evolution improving on environmental studies.Comment: 5 pages, 3. figures and supplemental material with 11 page, 4 figuresand 2 table

Hybrid-bias and displacement emulators for field-level modelling of galaxy clustering in real and redshift space

Recently, hybrid bias expansions have emerged as a powerful approach to modelling the way in which galaxies are distributed in the Universe. Similarly, field-level emulators have recently become possible thanks to advances in machine learning and $N$-body simulations. In this paper we explore whether both techniques can be combined to provide a field-level model for the clustering of galaxies in real and redshift space. Specifically, here we will demonstrate that field-level emulators are able to accurately predict all the operators of a $2^{\rm nd}$-order hybrid bias expansion. The precision achieved in real and redshift space is similar to that obtained for the nonlinear matter power spectrum. This translates to roughly 1-2\% precision for the power spectrum of a BOSS and a Euclid-like galaxy sample up to $k\sim 0.6 h^{-1}$Mpc. Remarkably, this combined approach also delivers precise predictions for field-level galaxy statistics. Despite all these promising results, we detect several areas where further improvements are required. Therefore, this work serves as a road-map for the developments required for a more complete exploitation of upcoming large-scale structure surveys.Comment: 13 pages, 9 figure

The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: a tomographic analysis of structure growth and expansion rate from anisotropic galaxy clustering

We perform a tomographic analysis of structure growth and expansion rate from the anisotropic galaxy clustering of the combined sample of Baryon Oscillation Spectroscopic Survey (BOSS) Data Release 12, which covers the redshift range of $0.2<z<0.75$. In order to extract the redshift information of anisotropic galaxy clustering, we analyse this data set in nine overlapping redshift slices in configuration space and perform the joint constraints on the parameters $(D_V, F_{\mathrm{AP}}, f\sigma_8)$ using the correlation function multipoles. The analysis pipeline is validated using the MultiDark-Patchy mock catalogues. We obtain a measurement precision of $1.5\%-2.9\%$ for $D_V$, $5.2\%-9\%$ for $F_{\mathrm{AP}}$ and $13.3\%-24\%$ for $f \sigma_8$, depending on the effective redshift of the slices. We report a joint measurement of $(D_V, F_{\mathrm{AP}}, f\sigma_8)$ with the full covariance matrix in nine redshift slices. We use our joint BAO and RSD measurement combined with external datasets to constrain the gravitational growth index $\gamma$, and find $\gamma=0.656 \pm 0.057$, which is consistent with the $\Lambda$CDM prediction within 95\% CL.Comment: 8 pages, 8 figures, 2 tables, accepted for publication MNRAS. The measured results including the full covariance matrices are made available at https://github.com/ytcosmo/TomoBAORSD and tomographic clustering data used in this work is available at https://sdss3.org//science/boss_publications.ph

Introducción de una nueva línea de negocio de impresión digital

Este trabajo, trata de analizar la introducción de una nueva línea de negocio de impresión en una empresa ya consolidada dedicada a la encuadernación en el sector artes gráficas. Empezamos analizando el entorno de la empresa y su posicionamiento, posteriormente se procede a continuar con un análisis económico, donde se hace referencia a todo los necesario para la puesta en marcha de la nueva línea, incluyendo todos los datos referentes a la inversión. Finalmente, tras el análisis económico, procedemos al estudio de viabilidad del negocio, donde tras exponerlo a diferentes condiciones se decide si el proyecto debe realizarse

The Bacco Simulation Project: Bacco Hybrid Lagrangian Bias Expansion Model in Redshift Space

We present an emulator that accurately predicts the power spectrum of galaxies in redshift space as a function of cosmological parameters. Our emulator is based on a 2nd-order Lagrangian bias expansion that is displaced to Eulerian space using cosmological $N$-body simulations. Redshift space distortions are then imprinted using the non-linear velocity field of simulated particles and haloes. We build the emulator using a forward neural network trained with the simulations of the BACCO project, which covers an 8-dimensional parameter space including massive neutrinos and dynamical dark energy. We show that our emulator provides unbiased cosmological constraints from the monopole, quadrupole, and hexadecapole of a mock galaxy catalogue that mimics the BOSS-CMASS sample down to nonlinear scales ($k\sim0.6$[$h/$Mpc]$^{3}$). This work opens up the possibility of robustly extracting cosmological information from small scales using observations of the large-scale structure of the Universe.Comment: 16 pages, 9 figure

UNIT project: Universe NN-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.Comment: 12 pages, 9 figures. This version matches the one accepted by MNRAS. The data from this project are publicly available at: http://www.unitsims.or