The Spitzer/IRAC Legacy over the GOODS Fields: Full-depth 3.6, 4.5, 5.8, and 8.0 μm Mosaics and Photometry for >9000 Galaxies at z ∼ 3.5–10 from the GOODS Reionization Era Wide-area Treasury from Spitzer (GREATS)

We present the deepest Spitzer/InfraRed Array Camera (IRAC) 3.6, 4.5, 5.8, and 8.0 μm wide-area mosaics yet over the Great Observatories Origins Deep Survey (GOODS)-N and GOODS-S fields as part of the GOODS Reionization Era wide-Area Treasury from Spitzer (GREATS) project. We reduced and mosaicked in a self-consistent way observations taken by the 11 different Spitzer/IRAC programs over the two GOODS fields from 12 yr of Spitzer cryogenic and warm-mission data. The cumulative depth in the 3.6 μm and 4.5 μm bands amounts to ∼4260 hr, ∼1220 hr of which are new very deep observations from the GREATS program itself. In the deepest area, the full-depth mosaics reach ≳200 hr over an area of ∼100 arcmin2, corresponding to a sensitivity of ∼29 AB magnitude at 3.6 μm (1σ for point sources). Archival cryogenic 5.8 μm and 8.0 μm band data (a cumulative 976 hr) are also included in the release. The mosaics are projected onto the tangential plane of the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey/GOODS at a 0.″3 pixel−1 scale. This paper describes the methodology enabling, and the characteristics of, the public release of the mosaic science images, the corresponding coverage maps in the four IRAC bands, and the empirical point-spread functions (PSFs). These PSFs enable mitigation of the source blending effects by taking into account the complex position-dependent variation in the IRAC images. The GREATS data products are in the Infrared Science Archive. We also release the deblended 3.6–8.0 μm photometry 9192 Lyman-break galaxies at z ∼ 3.5–10. GREATS will be the deepest mid-infrared imaging until the James Webb Space Telescope and, as such, constitutes a major resource for characterizing early galaxy assembly.

On the Constraints of Galaxy Assembly Bias in Velocity Space

If the formation of central galaxies in dark matter haloes traces the assembly history of their host haloes, in haloes of fixed mass, central galaxy clustering may show dependence on properties indicating their formation history. Such a galaxy assembly bias effect has been investigated by Lin et al. (2016), with samples of central galaxies constructed in haloes of similar mass and with mean halo mass verified by galaxy lensing measurements, and no significant evidence of assembly bias is found from the analysis of the projected two-point correlation functions of early- and late-forming central galaxies. In this work, we extend the the investigation of assembly bias effect from real space to redshift (velocity) space, with an extended construction of early- and late-forming galaxies. We carry out halo occupation distribution modelling to constrain the galaxy-halo connection to see whether there is any sign of the effect of assembly bias. We find largely consistent host halo mass for early- and late-forming central galaxies, corroborated by lensing measurements. The central velocity bias parameters, which are supposed to characterise the mutual relaxation between central galaxies and their host haloes, are inferred to overlap between early- and late-forming central galaxies. However, we find a large amplitude of velocity bias for early-forming central galaxies (e.g. with central galaxies moving at more than 50% that of dark matter velocity dispersion inside host haloes), which may signal an assembly bias effect. A large sample with two-point correlation functions and other clustering measurements and improved modelling will help reach a conclusive result.

Galaxy assembly bias and large-scale distribution: a comparison between IllustrisTNG and a semi-analytic model

In this work, we compare large scale structure observables for stellar mass selected samples at z = 0, as predicted by two galaxy models, the hydrodynamical simulation IllustrisTNG and the Santa-Cruz semi-analytic model (SC-SAM). Although both models have been independently calibrated to match observations, rather than each other, we find good agreement between the two models for two-point clustering and galaxy assembly bias signatures. The models also show a qualitatively similar response of occupancy and clustering to secondary halo paramaters other than mass, such as formation history and concentration, although with some quantitative differences. Thus, our results demonstrate that the galaxy-halo relationships in SC-SAM and TNG are quite similar to first order. However, we also find areas in which the models differ. For example, we note a strong correlation between halo gas content and environment in TNG, which is lacking in the SC-SAM, as well as differences in the occupancy predictions for low-mass haloes. Moreover, we show that higher-order statistics, such as cumulants of the density field, help to accurately describe the galaxy distribution and discriminate between models that show degenerate behaviour for two-point statistics. Our results suggest that SAMs are a promising cost-effective and intuitive method for generating mock catalogues for next generation cosmological surveys.

A flexible subhalo abundance matching model for galaxy clustering in redshift space

ABSTRACT We develop an extension of subhalo abundance matching (SHAM) capable of accurately reproducing the real and redshift-space clustering of galaxies in a state-of-the-art hydrodynamical simulation. Our method uses a low-resolution gravity-only simulation and it includes orphan and tidal disruption prescriptions for satellite galaxies, and a flexible amount of galaxy assembly bias. Furthermore, it includes recipes for star formation rate (SFR) based on the dark matter accretion rate. We test the accuracy of our model against catalogues of stellar-mass- and SFR-selected galaxies in the TNG300 hydrodynamic simulation. By fitting a small number of free parameters, our extended SHAM reproduces the projected correlation function and redshift-space multipoles for number densities $10^{-3} - 10^{-2}\, h^{3}{\rm Mpc}^{-3}$, at z = 1 and z = 0, and for scales r ∈ [0.3 − 20]h−1Mpc. Simultaneously, the SHAM results also retrieve the correct halo occupation distribution, the level of galaxy assembly bias, and higher order statistics present in the TNG300 galaxy catalogues. As an application, we show that our model simultaneously fits the projected correlation function of the SDSS in three disjoint stellar mass bins, with an accuracy similar to that of TNG300 galaxies. This SHAM extension can be used to get accurate clustering prediction even when using low and moderate-resolution simulations.

Predicting halo occupation and galaxy assembly bias with machine learning

Understanding the impact of halo properties beyond halo mass on the clustering of galaxies (namely galaxy assembly bias) remains a challenge for contemporary models of galaxy clustering. We explore the use of machine learning to predict the halo occupations and recover galaxy clustering and assembly bias in a semi-analytic galaxy formation model. For stellar mass selected samples, we train a random forest algorithm on the number of central and satellite galaxies in each dark matter halo. With the predicted occupations, we create mock galaxy catalogues and measure the clustering and assembly bias. Using a range of halo and environment properties, we find that the machine learning predictions of the occupancy variations with secondary properties, galaxy clustering, and assembly bias are all in excellent agreement with those of our target galaxy formation model. Internal halo properties are most important for the central galaxies prediction, while environment plays a critical role for the satellites. Our machine learning models are all provided in a usable format. We demonstrate that machine learning is a powerful tool for modelling the galaxy–halo connection, and can be used to create realistic mock galaxy catalogues which accurately recover the expected occupancy variations, galaxy clustering, and galaxy assembly bias, imperative for cosmological analyses of upcoming surveys.

Multi-wavelength mock galaxy catalogs of the low-redshift Universe

We present a new suite of mock galaxy catalogs mimicking the low-redshift Universe, based on an updated halo occupation distribution (HOD) model and a scaling relation between optical properties and the neutral hydrogen (Hi) content of galaxies. Our algorithm is constrained by observations of the luminosity function and luminosity- and colour-dependent clustering of SDSS galaxies, as well as the Hi mass function and Hi-dependent clustering of massive Hi-selected galaxies in the ALFALFA survey. Mock central and satellite galaxies with realistic values of r-band luminosity, g − r and u − r colour, stellar mass and Hi mass are populated in an N-body simulation, inheriting a number of properties of the density and tidal environment of their host halos. The host halo of each central galaxy is also ‘baryonified’ with realistic spatial distributions of stars as well as hot and cold gas, along with the corresponding rotation curve. Our default HOD assumes that galaxy properties are a function of group halo mass alone, and can optionally include effects such as galactic conformity and colour-dependent galaxy assembly bias. The mocks predict the relation between the stellar mass and Hi mass of massive Hi galaxies, as well as the 2-point cross-correlation function of spatially co-located optical and Hi-selected samples. They enable novel null tests for galaxy assembly bias, provide predictions for the Hi velocity width function, and clarify the origin and universality of the radial acceleration relation in the ΛCDM framework.

The kinematics of globular cluster populations in the E-MOSAICS simulations and their implications for the assembly history of the Milky Way

We present a detailed comparison of the Milky Way (MW) globular cluster (GC) kinematics with the 25 Milky Way-mass cosmological simulations from the E-MOSAICS project. While the MW falls within the kinematic distribution of GCs spanned by the simulations, the relative kinematics of its metal-rich ($[\rm {Fe}/\rm {H}]>-1.2$) versus metal-poor ($[\rm {Fe}/\rm {H}]<-1.2$), and inner (r < 8 kpc) versus outer (r > 8 kpc) populations are atypical for its mass. To understand the origins of these features, we perform a comprehensive statistical analysis of the simulations, and find 18 correlations describing the assembly of L* galaxies and their dark matter haloes based on their GC population kinematics. The correlations arise because the orbital distributions of accreted and in-situ GCs depend on the masses and accretion redshifts of accreted satellites, driven by the combined effects of dynamical fraction, tidal stripping, and dynamical heating. Because the kinematics of in-situ/accreted GCs are broadly traced by the metal-rich/metal-poor and inner/outer populations, the observed GC kinematics are a sensitive probe of galaxy assembly. We predict that relative to the population of L* galaxies, the MW assembled its dark matter and stellar mass rapidly through a combination of in-situ star formation, more than a dozen low-mass mergers, and 1.4 ± 1.2 early (z = 3.1 ± 1.3) major mergers. The rapid assembly period ended early, limiting the fraction of accreted stars. We conclude by providing detailed quantitative predictions for the assembly history of the MW.

On particle acceleration and transport in plasmas in the Galaxy: theory and observations

Accelerated particles are ubiquitous in the Cosmos and play a fundamental role in many processes governing the evolution of the Universe at all scales, from the sub-AU scale relevant for the formation and evolution of stars and planets to the Mpc scale involved in Galaxy assembly. We reveal the presence of energetic particles in many classes of astrophysical sources thanks to their production of non-thermal radiation, and we detect them directly at the Earth as cosmic rays. In the last two decades both direct and indirect observations have provided us a wealth of new, high-quality data about cosmic rays and their interactions both in sources and during propagation, in the Galaxy and in the Solar System. Some of the new data have confirmed existing theories about particle acceleration and propagation and their interplay with the environment in which they occur. Some others have brought about interesting surprises, whose interpretation is not straightforward within the standard framework and may require a change of paradigm in terms of our ideas about the origin of cosmic rays of different species or in different energy ranges. In this article, we focus on cosmic rays of galactic origin, namely with energies below a few petaelectronvolts, where a steepening is observed in the spectrum of energetic particles detected at the Earth. We review the recent observational findings and the current status of the theory about the origin and propagation of galactic cosmic rays.

Evidence for galaxy assembly bias in BOSS CMASS redshift-space galaxy correlation function

ABSTRACT Building accurate and flexible galaxy–halo connection models is crucial in modelling galaxy clustering on non-linear scales. Recent studies have found that halo concentration by itself cannot capture the full galaxy assembly bias effect and that the local environment of the halo can be an excellent indicator of galaxy assembly bias. In this paper, we propose an extended halo occupation distribution (HOD) model that includes both a concentration-based assembly bias term and an environment-based assembly bias term. We use this model to achieve a good fit (χ2/degrees of freedom = 1.35) on the 2D redshift-space two-point correlation function (2PCF) of the Baryon Oscillation Spectroscopic Survey (BOSS) CMASS galaxy sample. We find that the inclusion of both assembly bias terms is strongly favoured by the data and the standard five-parameter HOD model is strongly rejected. More interestingly, the redshift-space 2PCF drives the assembly bias parameters in a way that preferentially assigns galaxies to lower mass haloes. This results in galaxy–galaxy lensing predictions that are within 1σ agreement with the observation, alleviating the perceived tension between galaxy clustering and lensing. We also showcase a consistent 3σ–5σ preference for a positive environment-based assembly bias that persists over variations in the fit. We speculate that the environmental dependence might be driven by underlying processes such as mergers and feedback, but might also be indicative of a larger halo boundaries such as the splashback radius. Regardless, this work highlights the importance of building flexible galaxy–halo connection models and demonstrates the extra constraining power of the redshift-space 2PCF.

Dissecting and modelling galaxy assembly bias

ABSTRACT Understanding the galaxy-halo connection is fundamental for contemporary models of galaxy clustering. The extent to which the haloes’ assembly history and environment impact galaxy clustering (a.k.a. galaxy assembly bias; GAB), remains a complex and challenging problem. Using a semi-analytic galaxy formation model, we study the individual contributions of different secondary halo properties to the GAB signal. These are obtained by comparing the clustering of stellar-mass selected samples to that of shuffled samples where the galaxies are randomly reassigned to haloes of fixed mass and a specified secondary halo property. We explore a large range of internal halo properties and environmental measures. We find that commonly used properties like halo age or concentration amount to only 20–30 per cent of the signal, while the smoothed matter density or the tidal anisotropy can account for the full level of GAB (though care should be given to the specific definition). For the ‘successful’ measures, we examine the occupancy variations and the associated changes in the halo occupation function parameters. These are used to create mock catalogues that reproduce the full level of GAB. Finally, we propose a practical modification of the standard halo occupation distribution model, which can be tuned to any level of assembly bias. Fitting the parameters to our semi-analytic model, we demonstrate that the corresponding mock catalogue recovers the target level of GAB as well as the occupancy variations. Our results enable producing realistic mock catalogues and directly inform theoretical modelling of assembly bias and attempts to detect it in the Universe.