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We present a comprehensive study of the star formation histories of massive-quenched galaxies at $z=3$ in 3 semi-analytic models (SHARK, GAEA, GALFORM) and 3 cosmological hydrodynamical simulations (EAGLE, Illustris-TNG, Simba). We study the predicted number density and stellar mass function of massive-quenched galaxies, their formation and quenching timescales and star-formation properties of their progenitors. Predictions are disparate in all these diagnostics, for instance: (i) some simulations reproduce the observed number density of very massive-quenched galaxies ($>10^{11}\rm M_{\odot}$) but underpredict the high density of intermediate-mass ones, while others fit well the lower masses but underpredict the higher ones; (ii) In most simulations, except for GAEA and EAGLE, most massive-quenched galaxies had starburst periods, with the most intense ones happening at $4300\rm M_{\odot}\,yr^{-1}$; (iii) quenching timescales are in the range $\approx 20-150$~Myr depending on the simulation; among other differences. These disparate predictions can be tied to the adopted Active Galactic Nuclei (AGN) feedback model. For instance, the explicit black-hole (BH) mass dependence to trigger the "radio mode" in Illustris-TNG and Simba makes it difficult to produce quenched galaxies with intermediate stellar masses, also leading to higher baryon collapse efficiencies ($\approx 15-30$%); while the strong bolometric luminosity dependence of the AGN outflow rate in GAEA leads to BHs of modest mass quenching galaxies. Current observations are unable to distinguish between these different predictions due to the small sample sizes. However, these predictions are testable with current facilities and upcoming observations, allowing a "true physics experiment" to be carried out., Comment: Submitted for publication in MNRAS. 32 pages (21 of main body and 11 of appendices). Comments welcome!

ANNZ is a fast and simple algorithm which utilises artificial neural networks (ANNs), it was known as one of the pioneers of machine learning approaches to photometric redshift estimation decades ago. We enhanced the algorithm by introducing new activation functions like tanh, softplus, SiLU, Mish and ReLU variants; its new performance is then vigorously tested on legacy samples like the Luminous Red Galaxy (LRG) and Stripe-82 samples from SDSS, as well as modern galaxy samples like the Physics of the Accelerating Universe Survey (PAUS). This work focuses on testing the robustness of activation functions with respect to the choice of ANN architectures, particularly on its depth and width, in the context of galaxy photometric redshift estimation. Our upgraded algorithm, which we named ANNZ+, shows that the tanh and Leaky ReLU activation functions provide more consistent and stable results across deeper and wider architectures with > 1 per cent improvement in root-mean-square error ($\sigma_{\textrm{RMS}}$) and 68th percentile error ($\sigma_{68}$) when tested on SDSS data sets. While assessing its capabilities in handling high dimensional inputs, we achieved an improvement of 11 per cent in $\sigma_{\textrm{RMS}}$ and 6 per cent in $\sigma_{68}$ with the tanh activation function when tested on the 40-narrowband PAUS dataset; it even outperformed ANNZ2, its supposed successor, by 44 per cent in $\sigma_{\textrm{RMS}}$. This justifies the effort to upgrade the 20-year-old ANNZ, allowing it to remain viable and competitive within the photo-z community today. The updated algorithm ANNZ+ is publicly available at https://github.com/imdadmpt/ANNzPlus., Comment: 38 pages, 9 figures, revised version submitted to JCAP

We present results from the latest version of the GAEA model of galaxy formation coupled with merger trees extracted from the P-Millennium Simulation (PMS), which provides a better mass resolution, a larger volume and assumes cosmological parameters consistent with latest results from the Planck mission. The model includes, at the same time, a treatment for the partition of cold gas into atomic and molecular (H$_2$) components; a better treatment for environmental processes acting on satellite galaxies; an updated modelling of cold gas accretion on Super-Massive Black Hole and relative AGN feedback on the host galaxy. We compare GAEA predictions based on the PMS, with model realizations based on other simulations in the Millennium Suite at different resolution, showing that the new model provides a remarkable consistency in the statistical properties of galaxy populations. We interpret this as due to the interplay between AGN feedback and H$_2$-based SFR (both acting as regulators of the cold gas content). We then compare model predictions with available data for the galaxy 2-point correlation function (2pCF) in the redshift range 0

Observations with the {\it James Webb Space Telescope} have revealed a high abundance of bright galaxies at redshift, $z\gtrsim 12$, which has been widely interpreted as conflicting with the $\Lambda$CDM model. In Cowley et al. (2018) predictions were made -- prior to the {\it JWST} observations -- for the expected abundance of these galaxies using the Durham semi-analytic galaxy formation model, {\sc galform}, which is known to produce a realistic population of galaxies at lower redshifts including the present day. Key to this model is the assumption of a ``top-heavy" initial mass function of stars formed in bursts (required to explain the number counts and redshift distribution of sub-millimetre galaxies). Here, we compare the rest-frame ultraviolet luminosity functions derived from {\it JWST} observations with those predicted by the Cowley et al. model up to $z=14$ and make further predictions for $z=16$. We find that below $z\sim 10$, the Cowley et al. predictions agree very well with observations, while agreement at $z\gtrsim12$ requires extending the model to take into account the timescale for the growth of obscuring dust grains at these very early times and its dependence on gas metallicity. We trace the evolution of these galaxies from $z=14$ to $z=0$ and find that their descendants typically reside in halos with a median mass $2.5\times 10^{13}\,h^{-1}\,\mathrm{M_{\odot}}$. The stellar masses of the descendants range from $3.2\times 10^{6}\,h^{-1}\,\mathrm{M_{\odot}}$ to $3.2\times 10^{11}\,h^{-1}\,\mathrm{M_{\odot}}$. Although these galaxies were all central galaxies at $z=14$, over half of their descendants end up as satellites in massive halos., Comment: 16 pages, 11 figures, accepted for publication in MNRAS

Narrowband galaxy surveys have recently gained interest as a promising method to achieve the necessary accuracy on the photometric redshift estimate of individual galaxies for stage-IV cosmological surveys. One key advantage is the ability to provide higher spectral resolution information about galaxies that should allow a more accurate and precise estimation of galaxy stellar population properties. However, the impact of adding narrow-band photometry on the stellar population properties estimate is largely unexplored. The scope of this work is two-fold: on one side, leveraging the predictive power of broad-band and narrow-band data to infer galaxy physical properties such as stellar masses, ages, star formation rates and metallicities. On the other hand, evaluating the improvement of performance in estimating galaxy properties when we use narrow-band data instead of broad-band. In this work we measure the stellar population properties of a sample of galaxies in the COSMOS field for which both narrowband and broadband data are available. In particular, we employ narrowband data from PAUS and broad-band data from CFHTLS. We use two different spectral energy distribution fitting codes to measure galaxy properties, namely CIGALE and Prospector. We find that the increased spectral resolution of narrow-band photometry does not yield a substantial improvement on constraining galaxy properties using spectral energy distribution fitting. Still we find that we obtain a more diverse distribution of metallicities and dust optical depths with cigale when employing the narrowband data. The effect is not as prominent as expected, which we relate this to the low narrowband SNR of a majority of the galaxies, the respective drawbacks of both codes as well as the coverage only in the optical regime. The measured properties are afterwards compared to the COSMOS2020 catalogue, showing good agreement., Comment: Published in A&A. 18 pages, 16 figures, 2 tables

We predict the surface density and clustering bias of H$\alpha$ emitting galaxies for the Euclid and Nancy Grace Roman Space Telescope redshift surveys using a new calibration of the GALFORM galaxy formation model. We generate 3000 GALFORM models to train an ensemble of deep learning algorithms to create an emulator. We then use this emulator in a Markov Chain Monte Carlo (MCMC) parameter search of an eleven-dimensional parameter space, to find a best-fitting model to a calibration dataset that includes local luminosity function data, and, for the first time, higher redshift data, namely the number counts of H$\alpha$ emitters. We discover tensions when exploring fits for the observational data when applying a heuristic weighting scheme in the MCMC framework. We find improved fits to the H$\alpha$ number counts while maintaining appropriate predictions for the local universe luminosity function. For a flux limited Euclid-like survey to a depth of 2$\times$10$^{-16}$ erg$^{-1}$ s$^{-1}$ cm$^{-2}$ for sources in the redshift range 0.9 < $z$ < 1.8, we estimate 2962-4331 H$\alpha$ emission-line sources deg$^{-2}$. For a Nancy Grace Roman survey, with a flux limit of 1$\times$10$^{-16}$ erg$^{-1}$ s$^{-1}$ cm$^{-2}$ and a redshift range 1.0 < $z$ < 2.0, we predict 6786-10322 H$\alpha$ emission-line sources deg$^{-2}$.

We explore the redshift evolution of the radio luminosity function (RLF) of star-forming galaxies using GALFORM, a semi-analytic model of galaxy formation and a dynamo model of the magnetic field evolving in a galaxy. Assuming energy equipartition between the magnetic field and cosmic rays, we derive the synchrotron luminosity of each sample galaxy. In a model where the turbulent speed is correlated with the star formation rate, the RLF is in fair agreement with observations in the redshift range $0 \leq z \leq 2$. At larger redshifts, the structure of galaxies, their interstellar matter and turbulence appear to be rather different from those at $z\lesssim2$, so that the turbulence and magnetic field models applicable at low redshifts become inadequate. The strong redshift evolution of the RLF at $0 \leq z \leq 2$ can be attributed to an increased number, at high redshift, of galaxies with large disc volumes and strong magnetic fields. On the other hand, in models where the turbulent speed is a constant or an explicit function of $z$, the observed redshift evolution of the RLF is poorly captured. The evolution of the interstellar turbulence and outflow parameters appear to be major (but not the only) drivers of the RLF changes. We find that both the small- and large-scale magnetic fields contribute to the RLF but the small-scale field dominates at high redshifts. Polarisation observations will therefore be important to distinguish these two components and understand better the evolution of galaxies and their nonthermal constituents., Comment: 19 pages, 8 figures. MNRAS, in press

This study investigates the clustering and bias of Luminous Red Galaxies (LRG) in the BOSS-LOWZ, -CMASS, -COMB, and eBOSS samples, using two types of simulated lightcones: (i) high-fidelity lightcones from Uchuu $N$-body simulation, employing SHAM technique to assign LRG to (sub)halos, and (ii) 16000 covariance lightcones from GLAM-Uchuu $N$-body simulations, including LRG using HOD data from Uchuu. Our results indicate that Uchuu and GLAM lightcones closely replicate BOSS/eBOSS data, reproducing correlation function and power spectrum across scales from redshifts $0.2$ to $1.0$, from $2$ to $150\,h^{-1}\mathrm{Mpc}$ in configuration space, from $0.005$ to $0.7\,h\mathrm{Mpc}^{-1}$ in Fourier space, and across different LRG stellar masses. Furthermore, comparing with existing MD-Patchy and EZmock BOSS/eBOSS lightcones based on approximate methods, our GLAM-Uchuu lightcones provide more precise clustering estimates. We identify significant deviations from observations within $20\,h^{-1}\mathrm{Mpc}$ scales in MD-Patchy and EZmock, with our covariance matrices indicating that these methods underestimate errors by between $10\%$ and $60\%$. Lastly, we explore the impact of cosmology on galaxy clustering. Our findings suggest that, given the current level of uncertainties in BOSS/eBOSS data, distinguishing models with and without massive neutrino effects on LSS is challenging. This paper highlights the Uchuu and GLAM-Uchuu simulations' robustness in verifying the accuracy of Planck cosmological parameters, providing a strong foundation for enhancing lightcone construction in future LSS surveys. We also demonstrate that generating thousands of galaxy lightcones is feasible using $N$-body simulations with adequate mass and force resolution.

We present a quantitative analysis of the properties of galaxies and structures evolving in universes dominated by different modified gravitational models, including two variants of the f(R)-gravity (F) and two of the Dvali-Gabdadze-Poratti (N) braneworld model, which respectively feature the chameleon and Vainshtein screening mechanisms. Using the Simulation HYdrodynamics BeyONd Einstein (SHYBONE) cosmological hydrodynamical full-physics simulations suite, we study the departures in the properties of galaxies residing in different environments with respect to the standard model (GR). Using two different criteria to compare, we find that structures formed within modified gravity tend to show a denser gas density profile than their GR counterparts. Within the different modified gravity models, N1 and F5 gravity models show greater departures from the standard model, with gas density profiles $\rho_{\rm IGM} \geq 30\%$ denser in the outskirts for the N1 model, and in the inner parts for the F5 model. Additionally, we find that haloes evolving in MG universes show, in general, larger quenched fractions than GR, reaching up to $20\%$ larger quenching fractions in F5 regardless of the stellar mass of the galaxy. With respect to the other models, F6, N1 and N5 show slightly larger quenched fractions, but no strong differences can be found. These results directly impact the colour distribution of galaxies, making them in MG models redder and older than their GR counterparts. Like GR, once the environment starts to play a role, galaxies rapidly get quenched and the differences between models vanish., Comment: 17 pages, 12 figures, submitted to MNRAS

We apply the marked correlation function test proposed by Armijo et al. (Paper I) to samples of luminous red galaxies (LRGs) from the final data release of the Sloan Digital Sky Survey (SDSS) III. The test assigns a density-dependent mark to galaxies in the estimation of the projected marked correlation function. Two gravity models are compared: general relativity (GR) and $f(R)$ gravity. We build mock catalogues which, by construction, reproduce the measured galaxy number density and two-point correlation function of the LRG samples, using the halo occupation distribution model (HOD). A range of HOD models give acceptable fits to the observational constraints, and this uncertainty is fed through to the error in the predicted marked correlation functions. The uncertainty from the HOD modelling is comparable to the sample variance for the SDSS-III LRG samples. Our analysis shows that current galaxy catalogues are too small for the test to distinguish a popular $f(R)$ model from GR. However, upcoming surveys with a better measured galaxy number density and smaller errors on the two-point correlation function, or a better understanding of galaxy formation, may allow our method to distinguish between viable gravity models., Comment: 7 pages, 4 Figures. Published by the Monthly Notices of the Royal Astronomical Society journal

Fast radio bursts (FRBs) are the first cosmological radio sources that vary on millisecond timescales, which makes them a unique probe of the Universe. Many proposed applications of FRBs require associated redshifts. These can only be obtained by localizing FRBs to their host galaxies and subsequently measuring their redshifts. Upcoming FRB surveys will provide arcsecond localization for many FRBs, not all of which can be followed up with dedicated optical observations. We aim to estimate the fraction of FRB hosts that will be catalogued with redshifts by existing and future optical surveys. We use the population synthesis code frbpoppy to simulate several FRB surveys, and the semi-analytical galaxy formation code GALFORM to simulate their host galaxies. We obtain redshift distributions for the simulated FRBs and the fraction with host galaxies in a survey. Depending on whether FRBs follow the cosmic star formation rate or stellar mass, 20 to 40 per cent of CHIME FRB hosts will be observed in an SDSS-like survey, all at $z<0.5$. The deeper DELVE survey will detect 63 to 85 per cent of ASKAP FRBs found in its coherent search mode. CHIME FRBs will reach $z\sim 3$, SKA1-Mid FRBs $z\sim 5$, but ground based follow-up is limited to $z\lesssim 1.5$. We discuss consequences for several FRB applications. If $\sim1/2$ of ASKAP FRBs have measured redshifts, 1000 detected FRBs can be used to constrain $\Omega_\text{b} h_{70}$ to within $\sim10$ per cent at 95 per cent credibility. We provide strategies for optimized follow-up, when building on data from existing surveys. Data and codes are made available., Comment: 18 pages, 16 figures, 4 tables, accepted for publication in MNRAS. Code available at https://github.com/JoschaJ/mockFRBhosts

We introduce a new scheme based on the marked correlation function to probe gravity using the large-scale structure of the Universe. We illustrate our approach by applying it to simulations of the metric-variation $f(R)$ modified gravity theory and general relativity (GR). The modifications to the equations in $f(R)$ gravity lead to changes in the environment of large-scale structures that could, in principle, be used to distinguish this model from GR. Applying the Monte Carlo Markov Chain algorithm, we use the observed number density and two-point clustering to fix the halo occupation distribution (HOD) model parameters and build mock galaxy catalogues from both simulations. To generate a mark for galaxies when computing the marked correlation function we estimate the local density using a Voronoi tessellation. Our approach allows us to isolate the contribution to the uncertainty in the predicted marked correlation function that arises from the range of viable HOD model parameters, in addition to the sample variance error for a single set of HOD parameters. This is critical for assessing the discriminatory power of the method. In a companion paper we apply our new scheme to a current large-scale structure survey., Comment: 11 pages, 7 figures. Accepted for publication in the Monthly Notcies of the Royal Astronomical Society

In this series of papers we present an emulator-based halo model for the non-linear clustering of galaxies in modified gravity cosmologies. In the first paper, we present emulators for the following halo properties: the halo mass function, concentration-mass relation and halo-matter cross-correlation function. The emulators are trained on data extracted from the \textsc{FORGE} and \textsc{BRIDGE} suites of $N$-body simulations, respectively for two modified gravity (MG) theories: $f(R)$ gravity and the DGP model, varying three standard cosmological parameters $\Omega_{\mathrm{m0}}, H_0, \sigma_8$, and one MG parameter, either $\bar{f}_{R0}$ or $r_{\mathrm{c}}$. Our halo property emulators achieve an accuracy of $\lesssim 1\%$ on independent test data sets. We demonstrate that the emulators can be combined with a galaxy-halo connection prescription to accurately predict the galaxy-galaxy and galaxy-matter correlation functions using the halo model framework., Comment: 18 pages, 15 figures

In this series of papers, we present a simulation-based model for the non-linear clustering of galaxies based on separate modelling of clustering in real space and velocity statistics. In the first paper, we present an emulator for the real-space correlation function of galaxies, whereas the emulator of the real-to-redshift space mapping based on velocity statistics is presented in the second paper. Here, we show that a neural network emulator for real-space galaxy clustering trained on data extracted from the Dark Quest suite of N-body simulations achieves sub-per cent accuracies on scales $1 < r < 30 $ $h^{-1} \,\mathrm{Mpc}$, and better than $3\%$ on scales $r < 1$ $h^{-1}\mathrm{Mpc}$ in predicting the clustering of dark-matter haloes with number density $10^{-3.5}$ $(h^{-1}\mathrm{Mpc})^{-3}$, close to that of SDSS LOWZ-like galaxies. The halo emulator can be combined with a galaxy-halo connection model to predict the galaxy correlation function through the halo model. We demonstrate that we accurately recover the cosmological and galaxy-halo connection parameters when galaxy clustering depends only on the mass of the galaxies' host halos. Furthermore, the constraining power in $\sigma_8$ increases by about a factor of $2$ when including scales smaller than $5$ $h^{-1} \,\mathrm{Mpc}$. However, when mass is not the only property responsible for galaxy clustering, as observed in hydrodynamical or semi-analytic models of galaxy formation, our emulator gives biased constraints on $\sigma_8$. This bias disappears when small scales ($r < 10$ $h^{-1}\mathrm{Mpc}$) are excluded from the analysis. This shows that a vanilla halo model could introduce biases into the analysis of future datasets.

We use the GALFORM semi-analytical model of galaxy formation and the Planck-Millennium simulation to investigate the origins of stellar mass in galaxies and their spheroids. We compare the importance of mergers and disc instabilities, as well as the starbursts that they trigger. We find that the fraction of galaxy stellar mass formed \textit{ex situ} ($f_\mathrm{ex}$) increases sharply from $M_*=10^{11}$ M$_\odot$ upwards, reaching $80\%$ at $M_*=10^{11.3}$ M$_\odot$. For low-mass galaxies we find larger \textit{\textit{ex situ}} contributions at $z=0$ than in other models ($7$-$12\%$), with a decrease towards higher redshifts. The global \textit{ex situ} fraction of all stellar mass falls sharply with redshift, from $40\%$ at $z=0$ to $3\%$ at $z=10$. Major mergers contribute roughly half of the \textit{ex situ} mass, with minor mergers and smooth accretion of satellites both accounting for $\approx25\%$, almost independent of stellar mass and redshift. Mergers dominate in building up high-mass ($M_\mathrm{*,sph}>10^{11}$ M$_\odot$) and low-mass ($M_\mathrm{*,sph}<10^{8.5}$ M$_\odot$) spheroids. Disc instabilities and their associated starbursts dominate for intermediate-mass spheroids ($10^{8.5}

Conservative mass limits are often imposed on the dark matter halo catalogues extracted from N-body simulations. By comparing simulations with different mass resolutions, at $z=0$ we find that even for halos resolved by 100 particles, the lower resolution simulation predicts a cumulative halo abundance that is 5 per cent lower than in the higher resolution simulation. We propose a simple weighting scheme to utilise the halos that are usually regarded as being `sub-resolution'. With the scheme, we are able to use halos which contain only 11 particles to reproduce the clustering measured in the higher resolution simulation to within 5 per cent on scales down to $2 h^{-1}$ Mpc, thereby extending the useful halo resolution by a factor of ten below the mass at which the mass functions in the two simulations first start to deviate. The performance of the method is slightly worse at higher redshift. Our method allows a simulation to be used to probe a wider parameter space in clustering studies, for example, in a halo occupation distribution analysis. This reduces the cost of generating many simulations to estimate the covariance matrix on measurements or using a larger volume simulation to make large-scale clustering predictions., Comment: 5 pages, 3 figures. Accepted for publication in MNRAS

The coming generation of galaxy surveys will provide measurements of galaxy clustering with unprecedented accuracy and data size, which will allow us to test cosmological models at much higher precision than achievable previously. This means that we must have more accurate theoretical predictions to compare with future observational data. As a first step towards more accurate modelling of the redshift space distortions (RSD) of small-scale galaxy clustering in modified gravity (MG) cosmologies, we investigate the validity of the so-called Skew-T (ST) probability distribution function (PDF) of halo pairwise peculiar velocities in these models. We show that, combined with the streaming model of RSD, the ST PDF substantially improves the small-scale predictions by incorporating skewness and kurtosis, for both $\Lambda$CDM and two leading MG models: $f(R)$ gravity and the DGP braneworld model. The ST model reproduces the velocity PDF and redshift-space halo clustering measured from MG $N$-body simulations very well down to $\sim 5 \, h^{-1}\mathrm{Mpc}$. In particular, we investigate the enhancements of halo pairwise velocity moments with respect to $\Lambda$CDM for a larger range of MG variants than previous works, and present simple explanations to the behaviours observed. By performing a simple Fisher analysis, we find a significnat increase in constraining power to detect modifications of General Relativity by introducing small-scale information in the RSD analyses., Comment: 21 pages, 8+3 figures, accepted for publication in MNRAS

We present MG-GLAM, a code developed for the very fast production of full $N$-body cosmological simulations in modified gravity (MG) models. We describe the implementation, numerical tests and first results of a large suite of cosmological simulations for three classes of MG models with conformal coupling terms: the $f(R)$ gravity, symmetron and coupled quintessence models. Derived from the parallel particle-mesh code GLAM, MG-GLAM incorporates an efficient multigrid relaxation technique to solve the characteristic nonlinear partial differential equations of these models. For $f(R)$ gravity, we have included new variants to diversify the model behaviour, and we have tailored the relaxation algorithms to these to maintain high computational efficiency. In a companion paper, we describe versions of this code developed for derivative coupling MG models, including the Vainshtein- and K-mouflage-type models. MG-GLAM can model the prototypes for most MG models of interest, and is broad and versatile. The code is highly optimised, with a tremendous speedup of a factor of more than a hundred compared with earlier $N$-body codes, while still giving accurate predictions of the matter power spectrum and dark matter halo abundance. MG-GLAM is ideal for the generation of large numbers of MG simulations that can be used in the construction of mock galaxy catalogues and the production of accurate emulators for ongoing and future galaxy surveys., Comment: 54 pages, 14 figures; this paper is the twin paper of arXiv:2110.00566 submitted to arXiv on the same day, and the two papers have identical texts in part

We present MG-GLAM, a code developed for the very fast production of full $N$-body cosmological simulations in modified gravity (MG) models. We describe the implementation, numerical tests and first results of a large suite of cosmological simulations for two broad classes of MG models with derivative coupling terms -- the Vainshtein- and Kmouflage-type models -- which respectively features the Vainshtein and Kmouflage screening mechanism. Derived from the parallel particle-mesh code GLAM, MG-GLAM incorporates an efficient multigrid relaxation technique to solve the characteristic nonlinear partial differential equations of these models. For Kmouflage, we have proposed a new algorithm for the relaxation solver, and run the first simulations of the model to understand its cosmological behaviour. In a companion paper, we describe versions of this code developed for conformally-coupled MG models, including several variants of $f(R)$ gravity, the symmetron model and coupled quintessence. Altogether, MG-GLAM has so far implemented the prototypes for most MG models of interest, and is broad and versatile. The code is highly optimised, with a tremendous (over two orders of magnitude) speedup when comparing its running time with earlier $N$-body codes, while still giving accurate predictions of the matter power spectrum and dark matter halo abundance. MG-GLAM is ideal for the generation of large numbers of MG simulations that can be used in the construction of mock galaxy catalogues and accurate emulators for ongoing and future galaxy surveys., Comment: 48 pages, 12 figures. This paper is the twin paper of arxiv:2110.00328 submitted to arXiv on the same day, and the two papers have identical texts in part

We present a study of galaxy mergers up to $z=10$ using the Planck Millennium cosmological dark matter simulation and the {\tt GALFORM} semi-analytical model of galaxy formation. Utilising the full ($800$ Mpc)$^3$ volume of the simulation, we studied the statistics of galaxy mergers in terms of merger rates and close pair fractions. We predict that merger rates begin to drop rapidly for high-mass galaxies ($M_*>10^{11.3}-10^{10.5}$ $M_\odot$ for $z=0-4$), as a result of the exponential decline in the galaxy stellar mass function. The predicted merger rates increase and then turn over with increasing redshift, by $z=3.5$, in disagreement with hydrodynamical simulations and semi-empirical models. In agreement with most other models and observations, we find that close pair fractions flatten or turn over at some redshift (dependent on the mass selection). We conduct an extensive comparison of close pair fractions, and highlight inconsistencies among models, but also between different observations. We provide a fitting formula for the major merger timescale for close galaxy pairs, in which the slope of the stellar mass dependence is redshift dependent. This is in disagreement with previous theoretical results that implied a constant slope. Instead we find a weak redshift dependence only for massive galaxies ($M_*>10^{10}$ M$_\odot$): in this case the merger timescale varies approximately as $M_*^{-0.55}$. We find that close pair fractions and merger timescales depend on the maximum projected separation as $r_\mathrm{max}^{1.32}$. This is in agreement with observations of small-scale clustering of galaxies, but is at odds with the linear dependence on projected separation that is often assumed., Comment: Accepted for publication in MNRAS

We characterise the selection cuts and clustering properties of a magnitude-limited sample of bright galaxies that is part of the Bright Galaxy Survey (BGS) of the Dark Energy Spectroscopic Instrument (DESI) using the ninth data release of the Legacy Imaging Surveys (DR9). We describe changes in the DR9 selection compared to the DR8 one as explored in Ruiz-Macias et al. (2021). We also compare the DR9 selection in three distinct regions: BASS/MzLS in the north Galactic Cap (NGC), DECaLS in the NGC, and DECaLS in the south Galactic Cap (SGC). We investigate the systematics associated with the selection and assess its completeness by matching the BGS targets with the Galaxy and Mass Assembly (GAMA) survey. We measure the angular clustering for the overall bright sample (r $\leq$ 19.5) and as function of apparent magnitude and colour. This enables to determine the clustering strength and slope by fitting a power-law model that can be used to generate accurate mock catalogues for this tracer. We use a counts-in-cells technique to explore higher-order statistics and cross-correlations with external spectroscopic data sets in order to check the evolution of the clustering with redshift and the redshift distribution of the BGS targets using clustering-redshifts. While this work validates the properties of the BGS bright targets, the final target selection pipeline and clustering properties of the entire DESI BGS will be fully characterised and validated with the spectroscopic data of Survey Validation., Comment: 16 pages, 17 figures

We examine the effect of using different halo finders and merger tree building algorithms on galaxy properties predicted using the GALFORM semi-analytical model run on a high resolution, large volume dark matter simulation. The halo finders/tree builders HBT, ROCKSTAR, SUBFIND and VELOCIRAPTOR differ in their definitions of halo mass, on whether only spatial or phase-space information is used, and in how they distinguish satellite and main haloes; all of these features have some impact on the model galaxies, even after the trees are post-processed and homogenised by GALFORM. The stellar mass function is insensitive to the halo and merger tree finder adopted. However, we find that the number of central and satellite galaxies in GALFORM does depend slightly on the halo finder/tree builder. The number of galaxies without resolved subhaloes depends strongly on the tree builder, with VELOCIRAPTOR, a phase-space finder, showing the largest population of such galaxies. The distributions of stellar masses, cold and hot gas masses, and star formation rates agree well between different halo finders/tree builders. However, because VELOCIRAPTOR has more early progenitor haloes, with these trees GALFORM produces slightly higher star formation rate densities at high redshift, smaller galaxy sizes, and larger stellar masses for the spheroid component. Since in all cases these differences are small we conclude that, when all of the trees are processed so that the main progenitor mass increases monotonically, the predicted GALFORM galaxy populations are stable and consistent for these four halo finders/tree builders., Comment: 20 pages, 16 figures

High-resolution cosmological hydrodynamic simulations are currently limited to relatively small volumes due to their computational expense. However, much larger volumes are required to probe rare, overdense environments, and measure clustering statistics of the large scale structure. Typically, zoom simulations of individual regions are used to study rare environments, and semi-analytic models and halo occupation models applied to dark matter only (DMO) simulations are used to study the Universe in the large-volume regime. We propose a new approach, using a machine learning framework to explore the halo-galaxy relationship in the periodic EAGLE simulations, and zoom C-EAGLE simulations of galaxy clusters. We train a tree based machine learning method to predict the baryonic properties of galaxies based on their host dark matter halo properties. The trained model successfully reproduces a number of key distribution functions for an infinitesimal fraction of the computational cost of a full hydrodynamic simulation. By training on both periodic simulations as well as zooms of overdense environments, we learn the bias of galaxy evolution in differing environments. This allows us to apply the trained model to a larger DMO volume than would be possible if we only trained on a periodic simulation. We demonstrate this application using the $(800 \; \mathrm{Mpc})^3$ P-Millennium simulation, and present predictions for key baryonic distribution functions and clustering statistics from the EAGLE model in this large volume., Comment: 17 pages, 16 figures, Accepted to MNRAS. Updated Acknowledgements

We implement a sample-efficient method for rapid and accurate emulation of semi-analytical galaxy formation models over a wide range of model outputs. We use ensembled deep learning algorithms to produce a fast emulator of an updated version of the GALFORM model from a small number of training examples. We use the emulator to explore the model's parameter space, and apply sensitivity analysis techniques to better understand the relative importance of the model parameters. We uncover key tensions between observational datasets by applying a heuristic weighting scheme in a Markov chain Monte Carlo framework and exploring the effects of requiring improved fits to certain datasets relative to others. Furthermore, we demonstrate that this method can be used to successfully calibrate the model parameters to a comprehensive list of observational constraints. In doing so, we re-discover previous GALFORM fits in an automatic and transparent way, and discover an improved fit by applying a heavier weighting to the fit to the metallicities of early-type galaxies. The deep learning emulator requires a fraction of the model evaluations needed in similar emulation approaches, achieving an out-of-sample mean absolute error at the knee of the K-band luminosity function of 0.06 dex with less than 1000 model evaluations. We demonstrate that this is an extremely efficient, inexpensive and transparent way to explore multi-dimensional parameter spaces, and can be applied more widely beyond semi-analytical galaxy formation models., Comment: 21 pages, 15 figures, submitted to MNRAS

The Dark Energy Spectroscopic Instrument (DESI) will execute a nearly magnitude-limited survey of low redshift galaxies ($0.05 \leq z \leq 0.4$, median $z \approx 0.2$). Clustering analyses of this Bright Galaxy Survey (BGS) will yield the most precise measurements to date of baryon acoustic oscillations and redshift-space distortions at low redshift. DESI BGS will comprise two target classes: (i) BRIGHT ($r<19.5$~mag), and (ii) FAINT ($19.5

The next generation of spectroscopic surveys will target emission-line galaxies (ELGs) to produce constraints on cosmological parameters. We study the large scale structure traced by ELGs using a combination of a semi-analytical model of galaxy formation, a code that computes the nebular emission from HII regions using the properties of the interstellar medium, and a large-volume, high-resolution N-body simulation. We consider fixed number density samples where galaxies are selected by either their H$\alpha$, [OIII]$\lambda 5007$ or [OII]$\lambda \lambda 3727-3729$ emission line luminosities. We investigate the assembly bias signatures of these samples, and compare them to those of stellar mass and SFR selected samples. Interestingly, we find that the [OIII]- and [OII]-selected samples display scale-dependent bias on large scales and that their assembly bias signatures are also scale-dependent. Both these effects are more pronounced for lower number density samples. The [OIII] and [OII] emitters that contribute most to the scale dependence tend to have a low gas-phase metallicity and are preferentially found in low-density regions. We also measure the baryon acoustic oscillation (BAO) feature and the $\beta$ parameter related to the growth rate of overdensities. We find a slight tendency for the BAO peak to shift toward smaller scales for [OII] emitters and that $\beta$ is scale-dependent at large scales. Our results suggest that ELG samples include environmental effects that should be modelled in order to remove potential systematic errors that could affect the estimation of cosmological parameters., Comment: 15 pages, 12 figures

We present the steps taken to produce a reliable and complete input galaxy catalogue for the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey (BGS) using the photometric Legacy Survey DR8 DECam. We analyse some of the main issues faced in the selection of targets for the DESI BGS, such as star-galaxy separation, contamination by fragmented stars and bright galaxies. Our pipeline utilizes a new way to select BGS galaxies using Gaia photometry and we implement geometrical and photometric masks that reduce the number of spurious objects. The resulting catalogue is cross-matched with the Galaxy And Mass Assembly (GAMA) survey to assess the completeness of the galaxy catalogue and the performance of the target selection. We also validate the clustering of the sources in our BGS catalogue by comparing with mock catalogues and the Sloan Digital Sky Survey (SDSS) data. Finally, the robustness of the BGS selection criteria is assessed by quantifying the dependence of the target galaxy density on imaging and other properties. The largest systematic correlation we find is a 7 per cent suppression of the target density in regions of high stellar density., Comment: 23 pages, 18 Figures

We present -- and make publicly available -- accurate and precise photometric redshifts in the ACS footprint from the COSMOS field for objects with $i_{\mathrm{AB}}\leq 23$. The redshifts are computed using a combination of narrow band photometry from PAUS, a survey with 40 narrow bands spaced at $100\r{A}$ intervals covering the range from $4500\r{A}$ to $8500\r{A}$, and 26 broad, intermediate, and narrow bands covering the UV, visible and near infrared spectrum from the COSMOS2015 catalogue. We introduce a new method that models the spectral energy distributions (SEDs) as a linear combination of continuum and emission line templates and computes its Bayes evidence, integrating over the linear combinations. The correlation between the UV luminosity and the OII line is measured using the 66 available bands with the zCOSMOS spectroscopic sample, and used as a prior which constrains the relative flux between continuum and emission line templates. The flux ratios between the OII line and $\mathrm{H}_{\alpha}$, $\mathrm{H}_{\beta}$ and $\mathrm{OIII}$ are similarly measured and used to generate the emission line templates. Comparing to public spectroscopic surveys via the quantity $\Delta_z\equiv(z_{\mathrm{photo}}-z_{\mathrm{spec}})/(1+z_{\mathrm{spec}})$, we find the photometric redshifts to be more precise than previous estimates, with $\sigma_{68}(\Delta_z) \approx (0.003, 0.009)$ for galaxies at magnitude $i_{\mathrm{AB}}\sim18$ and $i_{\mathrm{AB}}\sim23$, respectively, which is $3\times$ and $1.66\times$ tighter than COSMOS2015. Additionally, we find the redshifts to be very accurate on average, yielding a median of the $\Delta_z$ distribution compatible with $|\mathrm{median}(\Delta_z)|\leq0.001$ at all redshifts and magnitudes considered. Both the added PAUS data and new methodology contribute significantly to the improved results., Comment: 21 pages, 16 figures

We carry out ``full-physics'' hydrodynamical simulations of galaxy formation in the normal-branch Dvali-Gabadadze-Porrati (nDGP) braneworld model using a new modified version of the {\sc Arepo} code and the IllustrisTNG galaxy formation model. We simulate two nDGP models (N5 and N1) which represent, respectively, weak and moderate departures from GR, in boxes of sizes $62\,h^{-1}{\rm Mpc}$ and $25\,h^{-1}{\rm Mpc}$ using $2\times512^3$ dark matter particles and initial gas cells. This allows us to explore, for the first time, the impact of baryonic physics on galactic scales in braneworld models of modified gravity and to make predictions on the stellar content of dark matter haloes and galaxy evolution through cosmic time in these models. We find significant differences between the GR and nDGP models in the power spectra and correlation functions of gas, stars and dark matter of up to $\sim 25$ per cent on large scales. Similar to their impact in the standard cosmological model ($\Lambda$CDM), baryonic effects can have a significant influence over the clustering of the overall matter distribution, with a sign that depends on scale. Studying the degeneracy between modified gravity and galactic feedback in these models, we find that these two physical effects on matter clustering can be cleanly disentangled, allowing for a method to accurately predict the matter power spectrum with baryonic effects included, without having to run hydrodynamical simulations. Depending on the braneworld model, we find differences compared with GR of up to $\sim15$ per cent in galaxy properties such as the stellar-to-halo-mass ratio, galaxy stellar mass function, gas fraction and star formation rate density. The amplitude of the fifth force is reduced by the presence of baryons in the very inner part of haloes, but this reduction quickly becomes negligible above $\sim0.1$ times the halo radius., Comment: 18 pages, 9 figures, matches with published version

Luminous red galaxies (LRGs) are one of the key tracers of the large-scale structure of the Universe used by galaxy surveys. Hence, it is important to make accurate predictions for their properties and clustering, including the errors on these statistics. Here, we describe a novel technique which uses the semi-analytical model of galaxy formation {\sc Galform}, embedded in the high-resolution $N$-body Planck-Millennium simulation, to populate a thousand halo catalogues generated using the Parallel-PM $N$-body {\sc glam} code. Our hybrid scheme allows us to make clustering predictions on scales that cannot be modelled in the original $N$-body simulation. LRGs are selected in the redshift range $z=0.6-1$ from the {\sc Galform} output using similar colour-magnitude cuts in the $r$, $z$ and $W1$ bands to those that will be applied in the Dark Energy Spectroscopic Instrument (DESI) survey. We find that the LRG-halo connection is non-trivial, leading to the prediction of a non-standard halo occupation distribution; in particular, the occupation of central galaxies does not reach unity for the most massive haloes, and drops with increasing mass. The {\sc glam} catalogues reproduce the abundance and clustering of the LRGs predicted by {\sc Galform}, and show good agreement with recent measurements of the clustering of DESI-like LRGs using photometric redshifts. We use the \glam{} mocks to compute the covariance matrices for the two-point correlation function and power spectrum of the LRGs and their background dark matter density field, revealing important differences. We also make predictions for the linear-growth rate and the baryon acoustic oscillations distances at $z=0.6$, $0.74$ and $0.93$. All DESI-like LRG catalogues are made publicly available., Comment: 22 pages, 18 figure, submitted to MNRAS, the galaxy catalogues are available at http://www.skiesanduniverses.org/

We explore how to mitigate the clustering distortions in Lyman-$\alpha$ emitters (LAEs) samples caused by the miss-identification of the Lyman-$\alpha$ (Ly$\alpha$) wavelength in their Ly$\alpha$ line profiles. We use the Ly$\alpha$ line profiles from our previous LAE theoretical model that includes radiative transfer in the interstellar and intergalactic mediums. We introduce a novel approach to measure the systemic redshift of LAEs from their Ly$\alpha$ line using neural networks. In detail, we assume that, for a fraction of the whole LAE population their systemic redshift is determined precisely through other spectral features. We then use this subset to train a neural network that predicts the Ly$\alpha$ wavelength given a Ly$\alpha$ line profile. We test two different training sets: i) the LAEs are selected homogeneously and ii) only the brightest LAEs are selected. In comparison with previous approaches in the literature, our methodology improves significantly both accuracy and precision in determining the Ly$\alpha$ wavelength. In fact, after applying our algorithm in ideal Ly$\alpha$ line profiles, we recover the clustering unperturbed down to 1cMpc/h. Then, we test the performance of our methodology in realistic Ly$\alpha$ line profiles by downgrading their quality. The machine learning techniques work well even if the Ly$\alpha$ line profile quality is decreased considerably. We conclude that LAE surveys such as HETDEX would benefit from determining with high accuracy the systemic redshift of a subpopulation and applying our methodology to estimate the systemic redshift of the rest of the galaxy sample., Comment: 24 Pages, 16 figures, a lot of fun

To understand the nature of the accelerated expansion of the Universe, we need to combine constraints on the expansion rate and growth of structure. The growth rate is usually extracted from three dimensional galaxy maps by exploiting the effects of peculiar motions on galaxy clustering. However, theoretical models of the probability distribution function (PDF) of galaxy pairwise peculiar velocities are not accurate enough on small scales to reduce the error on theoretical predictions to the level required to match the precision expected for measurements from future surveys. Here, we improve the modelling of the pairwise velocity distribution by using the Skew-T PDF, which has nonzero skewness and kurtosis. Our model accurately reproduces the redshift-space multipoles (monopole, quadrupole and hexadecapole) predicted by N-body simulations, above scales of about $10\,h^{-1}{\rm Mpc}$. We illustrate how a Taylor expansion of the streaming model can reveal the contributions of the different moments to the clustering multipoles, which are independent of the shape of the velocity PDF. The Taylor expansion explains why the Gaussian streaming model works well in predicting the first two redshift-space multipoles, although the velocity PDF is non-Gaussian even on large scales. Indeed, any PDF with the correct first two moments would produce precise results for the monopole down to scales of about $10\,h^{-1}{\rm Mpc}$, and for the quadrupole down to about $30\,h^{-1}{\rm Mpc}$. An accurate model for the hexadecapole needs to include higher-order moments., Comment: Accepted for publication in MNRAS

We investigate if, for a fixed number density of targets and redshift, there is an optimal way to select a galaxy sample in order to measure the baryon acoustic oscillation (BAO) scale, which is used as a standard ruler to constrain the cosmic expansion. Using the mock galaxy catalogue built by Smith et al. in the Millennium-XXL N-body simulation with a technique to assign galaxies to dark matter haloes based on halo occupation distribution modelling, we consider the clustering of galaxies selected by luminosity, colour and local density. We assess how well the BAO scale can be extracted by fitting a template to the power spectrum measured for each sample. We find that the BAO peak position is recovered equally well for samples defined by luminosity or colour, while there is a bias in the BAO scale recovered for samples defined by density. The BAO position is contracted to smaller scales for the densest galaxy quartile and expanded to large scales for the two least dense galaxy quartiles. For fixed galaxy number density, density-selected samples have higher uncertainties in the recovered BAO scale than luminosity- or colour-selected samples., Comment: 11 pages, 8 figures, 1 table, submitted to MNRAS

We present the first application of a variance-based sensitivity analysis (SA) to a model that aims to predict the evolution and properties of the whole galaxy population. SA is a well-established technique in other quantitative sciences, but is a relatively novel tool for the evaluation of astrophysical models. We perform a multi-parameter exploration of the GALFORM semi-analytic galaxy formation model, to compute how sensitive the present-day K-band luminosity function is to varying different model parameters. The parameter space is scanned using a low-discrepancy sampling technique proposed by Saltelli. We first demonstrate the usefulness of the SA approach by varying just two model parameters, one which controls supernova feedback and the other the heating of gas by AGN. The SA analysis matches our physical intuition regarding how these parameters affect the predictions for different parts of the galaxy luminosity function. We then use SA to compute Sobol' sensitivity indices varying seven model parameters, connecting the variance in the model output to the variance in the input parameters. The sensitivity is computed in luminosity bins, allowing us to probe the origin of the model predictions in detail. We discover that the SA correctly identifies the least- and most important parameters. Moreover, the SA also captures the combined responses of varying multiple parameters at the same time. Our study marks a much needed step away from the traditional "one-at-a-time" parameter variation often used in this area and improves the transparency of multi-parameter models of galaxy formation., Comment: 16 pages, 10 figures

We model the large-scale linear galaxy bias $b_g(x,z)$ as a function of redshift $z$ and observed absolute magnitude threshold $x$ for broadband continuum emission from the far infrared to ultra-violet, as well as for prominent emission lines, such as the H$\alpha$, H$\beta$, Lya and [OII] lines. The modelling relies on the semi-analytic galaxy formation model GALFORM, run on the state-of-the-art $N$-body simulation SURFS with the Planck 2015 cosmology. We find that both the differential bias at observed absolute magnitude $x$ and the cumulative bias for magnitudes brighter than $x$ can be fitted with a five-parameter model: $b_g(x,z)=a + b(1+z)^e(1 + \exp{[(x-c)d]})$. We also find that the bias for the continuum bands follows a very similar form regardless of wavelength due to the mixing of star-forming and quiescent galaxies in a magnitude limited survey. Differences in bias only become apparent when an additional colour separation is included, which suggest extensions to this work could look at different colours at fixed magnitude limits. We test our fitting formula against observations, finding reasonable agreement with some measurements within $1\sigma$ statistical uncertainties, and highlighting areas of improvement. We provide the fitting parameters for various continuum bands, emission lines and intrinsic galaxy properties, enabling a quick estimation of the linear bias in any typical survey of large-scale structure., Comment: Revised manuscript accepted for publication in MNRAS

The experiment to detect the global epoch of reionization signature (EDGES) collaboration reported the detection of a line at 78MHz in the sky-averaged spectrum due to neutral hydrogen (HI) 21-cm hyperfine absorption of cosmic microwave background photons at $z\sim 17$. This requires that the spin temperature of HI be coupled to the kinetic temperature of the gas at this $z$ through the scattering of Ly-$\alpha$ photons emitted by massive stars. To explain the experimental result, star formation needs to be sufficiently efficient at $z\sim 17$ and this can be used to constrain models in which small-scale structure formation is suppressed (DMF models), either due to dark matter free-streaming or non-standard inflationary dynamics. We combine simulations of structure formation with a simple recipe for star formation to investigate whether these models emit enough Ly-$\alpha$ photons to reproduce the experimental signal for reasonable values of the star formation efficiency, $f_\star$. We find that a thermal warm dark matter (WDM) model with mass $m_\mathrm{WDM}\sim 4.3\,\mathrm{keV}$ is consistent with the timing of the signal for $f_\star\lesssim 2\%$. The exponential growth of structure around $z\sim 17$ in such a model naturally generates a sharp onset of the absorption. A warmer model with $m_\mathrm{WDM}\sim 3\,\mathrm{keV}$ requires a higher star formation efficiency, $f_\star\sim 6\%$, which is a factor of few above predictions of current star formation models and observations of satellites in the Milky Way. However, uncertainties in the process of star formation at these $z$ do not allow to derive strong constrains on such models using 21-cm absorption line. The onset of the 21-cm absorption is generally faster in DMF compared to cold dark matter (CDM), unless some process significantly suppresses star formation in halos with masses below $\sim 10^8\,h^{-1}\,\mathrm{M}_\odot$., Comment: 20 pages, 3 figures. Minor changes to text and figures, some references added. Published in JCAP

Telescopes to be launched over the next decade-and-a-half, such as JWST, EUCLID, ATHENA and Lynx, promise to revolutionise the study of the high redshift Universe and greatly advance our understanding of the early stages of galaxy formation. We use a model that follows the evolution of the masses and spins of supermassive black holes (SMBHs) within a semi-analytic model of galaxy formation to make predictions for the Active Galactic Nucleus (AGN) luminosity function at $z\geq7$ in the broadband filters of JWST and EUCLID at near-infrared wavelengths, and ATHENA and Lynx at X-ray energies. The predictions of our model are relatively insensitive to the choice of seed black hole mass, except at the lowest luminosities ($L_{\mathrm{bol}}<10^{43}\mathrm{ergs^{-1}}$) and the highest redshifts ($z>10$). We predict that surveys with these different telescopes will select somewhat different samples of SMBHs, with EUCLID unveiling the most massive, highest accretion rate SMBHs, Lynx the least massive, lowest accretion rate SMBHs, and JWST and ATHENA covering objects inbetween. At $z=7$, we predict that typical detectable SMBHs will have masses, $M_{\mathrm{BH}}\sim10^{5-8}M_{\odot}$, and Eddington normalised mass accretion rates, $\dot{M}/\dot{M}_{\mathrm{Edd}}\sim0.6-2$. The SMBHs will be hosted by galaxies of stellar mass $M_{\star}\sim10^{8-10}M_{\odot}$, and dark matter haloes of mass $M_{\mathrm{halo}}\sim10^{11-12}M_{\odot}$. We predict that the detectable SMBHs at $z=10$ will have slightly smaller black holes, accreting at slightly higher Eddington normalised mass accretion rates, in slightly lower mass host galaxies compared to those at $z=7$, and reside in haloes of mass $M_{\mathrm{halo}}\sim10^{10-11}M_{\odot}$., Comment: MNRAS submitted. This is the second paper from a paper that has been split in two

We investigate a conceptual modification of the halo occupation distribution approach, using the halos' present-day maximal circular velocity, $\vmax$, as an alternative to halo mass. In particular, using a semi-analytic galaxy formation model applied to the Millennium WMAP7 simulation, we explore the extent that switching to $\vmax$ as the primary halo property incorporates the effects of assembly bias into the formalism. We consider fixed number density galaxy samples ranked by stellar mass and examine the variations in the halo occupation functions with either halo concentration or formation time. We find that using $\vmax$ results in a significant reduction in the occupancy variation of the central galaxies, particularly for concentration. The satellites occupancy variation on the other hand increases in all cases. We find effectively no change in the halo clustering dependence on concentration, for fixed bins of $\vmax$ compared to fixed halo mass. Most crucially, we calculate the impact of assembly bias on galaxy clustering by comparing the amplitude of clustering to that of a shuffled galaxy sample, finding that the level of galaxy assembly bias remains largely unchanged. Our results suggest that while using $\vmax$ as a proxy for halo mass diminishes some of occupancy variations exhibited in the galaxy-halo relation, it is not able to encapsulate the effects of assembly bias potentially present in galaxy clustering. The use of other more complex halo properties, such as $\vpeak$, the peak value of $\vmax$ over the assembly history, provides some improvement and warrants further investigation., Comment: 16 figures, 15 pages, submitted to ApJ

We test different implementations of the halo occupation distribution (HOD) model to reconstruct the spatial distribution of galaxies as predicted by a publicly available semi-analytical model (SAM). We compare the measured two-point correlation functions of the HOD mock catalogues and the SAM samples to quantify the fidelity of the reconstruction. We use fixed number density galaxy samples selected according to stellar mass or star formation rate (SFR). We develop three different schemes to populate haloes with galaxies with increasing complexity, considering the scatter of the satellite HOD as an additional parameter in the modelling. We first modify the SAM output, removing assembly bias and using a standard Navarro-Frenk-White density profile for the satellite galaxies as the target to reproduce with our HOD mocks. We find that all models give similar reproductions of the two-halo contribution to the clustering signal, but there are differences in the one-halo term. In particular, the HOD mock reproductions work equally well using either the HOD of central and satellites separately or using a model that also accounts for whether or not the haloes contain a central galaxy. We find that the HOD scatter does not have an important impact on the clustering predictions for stellar mass selected samples. For SFR selections, we obtain the most accurate results assuming a negative binomial distribution for the number of satellites in a halo. The scatter in the satellites HOD is a key consideration for HOD mock catalogues that mimic ELG or SFR selected samples in future galaxy surveys.

In the near future galaxy surveys will target Lyman alpha emitting galaxies (LAEs) to unveil the nature of the dark energy. It has been suggested that the observability of LAEs is coupled to the large scale properties of the intergalactic medium. Such coupling could introduce distortions into the observed clustering of LAEs, adding a new potential difficulty to the interpretation of upcoming surveys. We present a model of LAEs that incorporates Lyman-alpha radiative transfer processes in the interstellar and intergalactic medium. The model is implemented in the GALFORM semi-analytic model of galaxy of formation and evolution. We find that the radiative transfer inside galaxies produces selection effects over galaxy properties. In particular, observed LAEs tend to have low metallicities and intermediate star formation rates. At low redshift we find no evidence of a correlation between the spatial distribution of LAEs and the intergalactic medium properties. However, at high redshift the LAEs are linked to the line of sight velocity and density gradient of the intergalactic medium. The strength of the coupling depends on the outflow properties of the galaxies and redshift. This effect modifies the clustering of LAEs on large scales, adding non linear features. In particular, our model predicts modifications to the shape and position of the baryon acoustic oscillation peak. This work highlights the importance of including radiative transfer physics in the cosmological analysis of LAEs., Comment: 25 pages, 18 figures , a lot of love

We use two high resolution N-body simulations, one assuming general relativity and the other the Hu-Sawicki form of $f\left(R\right)$ gravity with $\vert \bar{f}_{R} \vert = 10^{-6}$, to investigate the concentration--formation time relation of dark matter haloes. We stack haloes in logarithmically spaced mass bins to fit median density profiles and extract median formation times. At fixed mass, haloes in modified gravity are more concentrated than those in GR, especially at low masses and at low redshift, and do not follow the concentration--formation time relation seen in GR. We assess the sensitivity of the relation to how concentration and formation time are defined, as well as to the segregation of the halo population by the amount of gravitational screening. We find a clear difference between halo concentrations and assembly histories displayed in modified gravity and those in GR. Existing models for the mass--concentration--redshift relation that have gained success in cold and warm dark matter models require revision in $f\left(R\right)$ gravity., Comment: 12 pages, 10 figures

We forecast the linear bias for H${\rm \alpha}$-emitting galaxies at high redshift. To simulate a Euclid-like and a WFIRST-like survey, we place galaxies into a large-volume dark matter halo lightcone by sampling a library of luminosity-dependent halo occupation distributions (HODs), which is constructed using a physically motivated galaxy formation model. We calibrate the dust attenuation in the lightcones such that they are able to reproduce the H{\alpha} luminosity function or the H{\alpha} cumulative number counts. The angle-averaged galaxy correlation function is computed for each survey in redshift slices of width $\Delta z = 0.2$. In each redshift bin the linear bias can be fitted with a single, scale-independent value that increases with increasing redshift. Fitting for the evolution of linear bias with redshift, we find that our Euclid-like and WFIRST-like surveys are both consistent within error with the relation $b(z) = 0.7z + 0.7$. Our bias forecasts are consistent with bias measurements from the HiZELS survey. We find that the Euclid-like and WFIRST-like surveys yield linear biases that are broadly consistent within error, most likely due to the HOD for the WFIRST-like survey having a steeper power-law slope towards larger halo masses., Comment: 30 pages including 8 pages of appendices. 17 figures. Accepted for publication in MNRAS following revisions

Measurements of redshift space distortions (RSD) provide a means to test models of gravity on large-scales. We use mock galaxy catalogues constructed from large N-body simulations of standard and modified gravity models to measure galaxy clustering in redshift space. We focus our attention on two of the most representative and popular families of modified gravity models: the Hu \& Sawicki $f(R)$ gravity and the normal branch of the DGP model. The galaxy catalogues are built using a halo occupation distribution (HOD) prescription with the HOD parameters in the modified gravity models tuned to match with the number density and the real-space clustering of {\sc boss-cmass} galaxies. We employ two approaches to model RSD: the first is based on linear perturbation theory and the second models non-linear effects on small-scales by assuming standard gravity and including biasing and RSD effects. We measure the monopole to real-space correlation function ratio, the quadrupole to monopole ratio, clustering wedges and multipoles of the correlation function and use these statistics to find the constraints on the distortion parameter, $\beta$. We find that the linear model fails to reproduce the N-body simulation results and the true value of $\beta$ on scales $s < 40\Mpch$, while the non-linear modelling of RSD recovers the value of $\beta$ on the scales of interest for all models. RSD on large scales ($s\gtrsim20$-$40\Mpch$) have been found to show significant deviations from the prediction of standard gravity in the DGP models. However, the potential to use RSD to constrain $f(R)$ models is less promising, due to the different screening mechanism in this model., Comment: 18 pages, 11 figures, submitted to MNRAS

We study the cosmic evolution of the magnetic fields of a large sample of spiral galaxies in a cosmologically representative volume by employing a semi-analytic galaxy formation model and numerical dynamo solver in tandem. We start by deriving time- and radius-dependent galaxy properties using the galform galaxy formation model, which are then fed into the nonlinear mean-field dynamo equations. These are solved to give the large-scale (mean) field as a function of time and galactocentric radius for a thin disc, assuming axial symmetry. A simple prescription for the evolution of the small-scale (random) magnetic field component is also adopted. We find that, while most massive galaxies are predicted to have large-scale magnetic fields at redshift z=0, a significant fraction of them are expected to contain negligible large-scale field. Our model indicates that, for most of the galaxies containing large-scale magnetic fields today, the mean-field dynamo becomes active at z<3. We compute the radial profiles of pitch angle, and find broad agreement with observational data for nearby galaxies., Comment: 19 pages, 10 figures. Accepted for publication in MNRAS

The recent discovery of gravitational waves marks the culmination of a sequence of successful tests of the general theory of relativity (GR) since its formulation in 1915. Yet these tests remain confined to the scale of stellar systems or the strong gravity regime. A departure from GR on larger, cosmological scales has been advocated by the proponents of modified gravity theories as an alternative to the Cosmological Constant to account for the observed cosmic expansion history. While indistinguishable in these terms by construction, such models on the other hand yield distinct values for the linear growth rate of density perturbations and, as a consequence, for the associated galaxy peculiar velocity field. Measurements of the resulting anisotropy of galaxy clustering, when spectroscopic redshifts are used to derive distances, have thus been proposed as a powerful probe of the validity of GR on cosmological scales. However, despite significant effort in modelling such redshift space distortions, systematic errors remain comparable to current statistical uncertainties. Here, we present the results of a different forward-modelling approach, which fully exploits the sensitivity of the galaxy velocity field to modifications of GR. We use state-of-the-art, high-resolution N-body simulations of a standard GR and a compelling f(R) model, one of GR's simplest variants, to build simulated catalogues of stellar-mass-selected galaxies through a robust match to the Sloan Digital Sky Survey observations. We find that, well within the uncertainty of this technique, f(R) fails to reproduce the observed redshift-space clustering on scales 1-10 Mpc/h. Instead, the standard LCDM GR model agrees impressively well with the data. This result provides a strong confirmation, on cosmological scales, of the robustness of Einstein's general theory of relativity., Comment: 35 Pages, 8 figures. Published in Nature Astronomy. This is the submitted version according to the journal policy. Full article available here (https://rdcu.be/7DiG)

The Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey (BGS) will be a survey of bright, low redshift galaxies, which is planned to cover an area of ~14,000 sq deg in 3 passes. Each pass will cover the survey area with ~2000 pointings, each of area ~8 sq deg. The BGS is currently proposed to consist of a bright high priority sample to an r-band magnitude limit r ~ 19.5, with a fainter low priority sample to r ~ 20. The geometry of the DESI fibre positioners in the focal plane of the telescope affects the completeness of the survey, and has a non-trivial impact on clustering measurements. Using a BGS mock catalogue, we show that completeness due to fibre assignment primarily depends on the surface density of galaxies. Completeness is high (>95%) in low density regions, but very low (<10%) in the centre of massive clusters. We apply the pair inverse probability (PIP) weighting correction to clustering measurements from a BGS mock which has been through the fibre assignment algorithm. This method is only unbiased if it is possible to observe every galaxy pair. To facilitate this, we randomly promote a small fraction of the fainter sample to be high priority, and dither the set of tile positions by a small angle. We show that inverse pair weighting combined with angular upweighting provides an unbiased correction to galaxy clustering measurements for the complete 3 pass survey, and also after 1 pass, which is highly incomplete., Comment: 18 pages, 17 figures, 4 tables, accepted for publication in MNRAS

We study potential systematic effects of assembly bias on cosmological parameter constraints from redshift space distortion measurements. We use a semi-analytic galaxy formation model applied to the Millennium N-body WMAP-7 simulation to study the effects of halo assembly bias on the redshift space distortions of the galaxy correlation function. We look at the pairwise velocities of galaxies living in haloes with concentrations and ages in the upper and lower quintiles, and find that the velocity differences between these are consistent with those reported for real-space clustering analyses, i.e. samples with higher clustering also exhibit stronger infall pairwise motions. This can also be seen in the monopole and quadrupole of the redshift-space correlation function. We find that regardless of the method of measurement, the changes in the $\beta$ parameter due to different secondary halo parameters fully tracks the change in the bias Parameter. Hence, assembly bias does not introduce detectable systematics in the inferred logarithmic growth factor., Comment: 15 pages, 12 figures.Submitted to MNRAS

We present predictions for the UV-to-mm extragalactic background light (EBL) from a recent version of the GALFORM semi-analytical model of galaxy formation which invokes a top-heavy stellar initial mass function (IMF) for galaxies undergoing dynamically-triggered bursts of star formation. We combine GALFORM with the GRASIL radiative transfer code for computing fully self-consistent UV-to-mm spectral energy distributions for each simulated galaxy, accounting for the absorption and re-emission of stellar radiation by interstellar dust. The predicted EBL is in near-perfect agreement with recent observations over the whole UV-to-mm spectrum, as is the evolution of the cosmic spectral energy distribution over the redshift range for which observations are available ($z\lesssim1$). We show that approximately 90~per~cent of the EBL is produced at $z<2$ although this shifts to higher redshifts for sub-mm wavelengths. We assess whether the top-heavy IMF in starbursts is necessary in order to reproduce the EBL at the same time as other key observables, and find that variant models with a universal solar-neighborhood IMF display poorer agreement with EBL observations over the whole UV-to-mm spectrum and fail to match the counts of galaxies in the sub-mm., Comment: 15 pages (+6 of Appendices), 9 figures (+5 in Appendices), Main results in Figs. 1 and 6. Accepted for publication in MNRAS