Approximate methods to populate dark-matter haloes with galaxies are of great utility to galaxy surveys. However, the limitations of simple halo occupation models (HODs) preclude a full use of small-scale galaxy clustering data and call for more sophisticated models. We study two galaxy populations, luminous red galaxies (LRGs) and star-forming emission-line galaxies (ELGs), at two epochs, z = 1 and z = 0, in the large-volume, high-resolution hydrodynamical simulation of the MillenniumTNG project. In a partner study we concentrated on the small-scale, one-halo regime down to r ∼ 0.1 h−1 Mpc, while here we focus on modelling galaxy assembly bias in the two-halo regime, r ≳ 1 h−1 Mpc. Interestingly, the ELG signal exhibits scale dependence out to relatively large scales (r ∼ 20 h−1 Mpc), implying that the linear bias approximation for this tracer is invalid on these scales, contrary to common assumptions. The 10–15 per cent discrepancy is only reconciled when we augment our halo occupation model with a dependence on extrinsic halo properties (‘shear’ being the best-performing one) rather than intrinsic ones (e.g. concentration, peak mass). We argue that this fact constitutes evidence for two-halo galaxy conformity. Including tertiary assembly bias (i.e. a property beyond mass and ‘shear’) is not an essential requirement for reconciling the galaxy assembly bias signal of LRGs, but the combination of external and internal properties is beneficial for recovering ELG the clustering. We find that centrals in low-mass haloes dominate the assembly bias signal of both populations. Finally, we explore the predictions of our model for higher order statistics such as nearest neighbour counts. The latter supplies additional information about galaxy assembly bias and can be used to break degeneracies between halo model parameters.

Extracting information from the total matter power spectrum with the precision needed for upcoming large cosmological surveys requires unraveling the complex effects of galaxy formation processes on the distribution of matter. In this work, we investigate the impact of baryonic physics on matter clustering at 𝑧 = 0 using a large library of power spectra from the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project, containing thousands of (25 ℎ −1 Mpc) 3 volume realizations with varying cosmology, initial random field, stellar and AGN feedback strength, sub-grid model implementation, and (magneto)hydrodynamics methods. We show that baryonic physics can profoundly affect matter clustering on scales 𝑘 0.1 ℎ Mpc −1 and the magnitude of this effect is highly dependent on the details of the galaxy formation implementation and variations of cosmological and astrophysical parameters. Increasing AGN feedback strength decreases halo baryon fractions and yields generally stronger suppression of power relative to N-body simulations, while stronger stellar feedback often results in weaker overall effects by suppressing black hole growth and therefore the impact of AGN feedback. We find a broad correlation between mean baryon fraction of massive halos (𝑀 200c > 10 13.5 M /ℎ) and suppression of matter clustering but with significant scatter compared to previous work owing to wider exploration of feedback parameters and cosmic variance effects. We show that a random forest regressor trained on the baryon content and abundance of halos across the full mass range 10 10 ≤ 𝑀 halo /M ℎ −1 < 10 14 can predict the effect of galaxy formation on the matter power spectrum on scales 𝑘 = 0.5-20 ℎ Mpc −1 , providing access to cosmological information in the highly non-linear regime.

Modern redshift surveys are tasked with mapping out the galaxy distribution over enormous distance scales. Existing hydrodynamical simulations, however, do not reach the volumes needed to match upcoming surveys. We present results for the clustering of galaxies using a new, large volume hydrodynamical simulation as part of the MillenniumTNG (MTNG) project. With a computational volume that is ≈15 times larger than the next largest such simulation currently available, we show that MTNG is able to accurately reproduce the observed clustering of galaxies as a function of stellar mass. When separated by colour, there are some discrepancies with respect to the observed population, which can be attributed to the quenching of satellite galaxies in our model. We combine MTNG galaxies with those generated using a semi-analytic model to emulate the sample selection of luminous red galaxies (LRGs) and emission-line galaxies (ELGs) and show that, although the bias of these populations is approximately (but not exactly) constant on scales larger than ≈10 Mpc, there is significant scale-dependent bias on smaller scales. The amplitude of this effect varies between the two galaxy types and between the semi-analytic model and MTNG. We show that this is related to the distribution of haloes hosting LRGs and ELGs. Using mock SDSS-like catalogues generated on MTNG lightcones, we demonstrate the existence of prominent baryonic acoustic features in the large-scale galaxy clustering. We also demonstrate the presence of realistic redshift space distortions in our mocks, finding excellent agreement with the multipoles of the redshift-space clustering measured in SDSS data.

A través de este artículo, se construyó una aproximación de carácter reflexivo, desde una perspectiva crítica, con el objetivo de evidenciar cuáles son las problemáticas y el cambio de contexto que introdujo la Cuarta Revolución Industrial en el mercado laboral. Para el efecto, se visibilizaron algunos casos prácticos ocurridos en otras jurisdicciones internacionales, así como el estudio de la normatividad legal y constitucional vigente en Colombia, por medio de la cual se pone de presente el vacío legal que actualmente existe en el marco del derecho laboral colectivo, respecto a las nuevas formas de trabajo que trajo la referida Cuarta Revolución Industrial.