Search

In this paper, we investigate the possibility of selecting high-redshift Lyman-Break Galaxies (LBG) using current and future broadband wide photometric surveys, such as UNIONS or the Vera C. Rubin LSST, using a Random Forest algorithm. This work is conducted in the context of future large-scale structure spectroscopic surveys like DESI-II, the next phase of the Dark Energy Spectroscopic Instrument (DESI), which will start around 2029. We use deep imaging data from HSC and CLAUDS on the COSMOS and XMM-LSS fields. To predict the selection performance of LBGs with image quality similar to UNIONS, we degrade the $u, g, r, i$ and $z$ bands to UNIONS depth. The Random Forest algorithm is trained with the $u,g,r,i$ and $z$ bands to classify LBGs in the $2.5 < z < 3.5$ range. We find that fixing a target density budget of $1,100$ deg$^{-2}$, the Random Forest approach gives a density of $z>2$ targets of $873$ deg$^{-2}$, and a density of $493$ deg$^{-2}$ of confirmed LBGs after spectroscopic confirmation with DESI. This UNIONS-like selection was tested in a dedicated spectroscopic observation campaign of 1,000 targets with DESI on the COSMOS field, providing a safe spectroscopic sample with a mean redshift of 3. This sample is used to derive forecasts for DESI-II, assuming a sky coverage of 5,000 deg$^2$. We predict uncertainties on Alcock-Paczynski parameters $\alpha_\perp$ and $\alpha_{\parallel}$ to be 0.7$\%$ and 1$\%$ for $2.6

On large scales, measurements of the Lyman-$\alpha$ forest offer insights into the expansion history of the Universe, while on small scales, these impose strict constraints on the growth history, the nature of dark matter, and the sum of neutrino masses. This work introduces ForestFlow, a cosmological emulator designed to bridge the gap between large- and small-scale Lyman-$\alpha$ forest analyses. Using conditional normalizing flows, ForestFlow emulates the 2 Lyman-$\alpha$ linear biases ($b_\delta$ and $b_\eta$) and 6 parameters describing small-scale deviations of the 3D flux power spectrum ($P_\mathrm{3D}$) from linear theory. These 8 parameters are modeled as a function of cosmology $\unicode{x2013}$ the small-scale amplitude and slope of the linear power spectrum $\unicode{x2013}$ and the physics of the intergalactic medium. Thus, in combination with a Boltzmann solver, ForestFlow can predict $P_\mathrm{3D}$ on arbitrarily large (linear) scales and the 1D flux power spectrum ($P_\mathrm{1D}$) $\unicode{x2013}$ the primary observable for small-scale analyses $\unicode{x2013}$ without the need for interpolation or extrapolation. Consequently, ForestFlow enables for the first time multiscale analyses. Trained on a suite of 30 fixed-and-paired cosmological hydrodynamical simulations spanning redshifts from $z=2$ to $4.5$, ForestFlow achieves $3$ and $1.5\%$ precision in describing $P_\mathrm{3D}$ and $P_\mathrm{1D}$ from linear scales to $k=5\,\mathrm{Mpc}^{-1}$ and $k_\parallel=4\,\mathrm{Mpc}^{-1}$, respectively. Thanks to its parameterization, the precision of the emulator is also similar for both ionization histories and two extensions to the $\Lambda$CDM model $\unicode{x2013}$ massive neutrinos and curvature $\unicode{x2013}$ not included in the training set. ForestFlow will be crucial for the cosmological analysis of Lyman-$\alpha$ forest measurements from the DESI survey., Comment: 17 pages, 11 figures. Submitted to A&A

When measuring the Baryon Acoustic Oscillations (BAO) scale from galaxy surveys, one typically assumes a fiducial cosmology when converting redshift measurements into comoving distances and also when defining input parameters for the reconstruction algorithm. A parameterised template for the model to be fitted is also created based on a (possibly different) fiducial cosmology. This model reliance can be considered a form of data compression, and the data is then analysed allowing that the true answer is different from the fiducial cosmology assumed. In this study, we evaluate the impact of the fiducial cosmology assumed in the BAO analysis of the Dark Energy Spectroscopic Instrument (DESI) survey Data Release 1 (DR1) on the final measurements in DESI 2024 III. We utilise a suite of mock galaxy catalogues with survey realism that mirrors the DESI DR1 tracers: the bright galaxy sample (BGS), the luminous red galaxies (LRG), the emission line galaxies (ELG) and the quasars (QSO), spanning a redshift range from 0.1 to 2.1. We compare the four secondary AbacusSummit cosmologies against DESI's fiducial cosmology (Planck 2018). The secondary cosmologies explored include a lower cold dark matter density, a thawing dark energy universe, a higher number of effective species, and a lower amplitude of matter clustering. The mocks are processed through the BAO pipeline by consistently iterating the grid, template, and reconstruction reference cosmologies. We determine a conservative systematic contribution to the error of $0.1\%$ for both the isotropic and anisotropic dilation parameters $\alpha_{\rm iso}$ and $\alpha_{\rm AP}$. We then directly test the impact of the fiducial cosmology on DESI DR1 data., Comment: Supporting publication of DESI 2024 III: Baryon Acoustic Oscillations from Galaxies and Quasars

We present a method to mitigate the effects of fiber assignment incompleteness in two-point power spectrum and correlation function measurements from galaxy spectroscopic surveys, by truncating small angular scales from estimators. We derive the corresponding modified correlation function and power spectrum windows to account for the small angular scale truncation in the theory prediction. We validate this approach on simulations reproducing the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1) with and without fiber assignment. We show that we recover unbiased cosmological constraints using small angular scale truncated estimators from simulations with fiber assignment incompleteness, with respect to standard estimators from complete simulations. Additionally, we present an approach to remove the sensitivity of the fits to high $k$ modes in the theoretical power spectrum, by applying a transformation to the data vector and window matrix. We find that our method efficiently mitigates the effect of fiber assignment incompleteness in two-point correlation function and power spectrum measurements, at low computational cost and with little statistical loss., Comment: 36 pages, 23 figures, typos corrected, clarifications added

The next generation of spectroscopic surveys is expected to achieve an unprecedented level of accuracy in the measurement of cosmological parameters. To avoid confirmation bias and thereby improve the reliability of these results, blinding procedures become a standard practice in the cosmological analyses of such surveys. Blinding is especially crucial when the impact of observational systematics is important relative to the cosmological signal, and a detection of that signal would have significant implications. This is the case for local primordial non-gaussianity, as probed by the scale-dependent bias of the galaxy power spectrum at large scales that are heavily sensitive to the dependence of the target selection on the imaging quality, known as imaging systematics. We propose a blinding method for the scale-dependent bias signature of local primordial non-gaussianity at the density field level which consists in generating a set of weights for the data that replicate the scale-dependent bias. The applied blinding is predictable, and can be straightforwardly combined with other catalog-level blinding procedures that have been designed for the baryon acoustic oscillation and redshift space distortion signals. The procedure is validated through simulations that replicate data from the first year of observation of the Dark Energy Spectroscopic Instrument, but may find applications to other upcoming spectroscopic surveys.

We present a computationally efficient galaxy archetype-based redshift estimation and spectral classification method for the Dark Energy Survey Instrument (DESI) survey. The DESI survey currently relies on a redshift fitter and spectral classifier using a linear combination of PCA-derived templates, which is very efficient in processing large volumes of DESI spectra within a short time frame. However, this method occasionally yields unphysical model fits for galaxies and fails to adequately absorb calibration errors that may still be occasionally visible in the reduced spectra. Our proposed approach improves upon this existing method by refitting the spectra with carefully generated physical galaxy archetypes combined with additional terms designed to absorb data reduction defects and provide more physical models to the DESI spectra. We test our method on an extensive dataset derived from the survey validation (SV) and Year 1 (Y1) data of DESI. Our findings indicate that the new method delivers marginally better redshift success for SV tiles while reducing catastrophic redshift failure by $10-30\%$. At the same time, results from millions of targets from the main survey show that our model has relatively higher redshift success and purity rates ($0.5-0.8\%$ higher) for galaxy targets while having similar success for QSOs. These improvements also demonstrate that the main DESI redshift pipeline is generally robust. Additionally, it reduces the false positive redshift estimation by $5-40\%$ for sky fibers. We also discuss the generic nature of our method and how it can be extended to other large spectroscopic surveys, along with possible future improvements., Comment: Accepted in AJ, 33 pages, 15 figures, 7 Tables, accepted version

We present the technical details on how large-scale structure (LSS) catalogs are constructed from redshifts measured from spectra observed by the Dark Energy Spectroscopic Instrument (DESI). The LSS catalogs provide the information needed to determine the relative number density of DESI tracers as a function of redshift and celestial coordinates and, e.g., determine clustering statistics. We produce catalogs that are weighted subsamples of the observed data, each matched to a weighted `random' catalog that forms an unclustered sampling of the probability density that DESI could have observed those data at each location. Precise knowledge of the DESI observing history and associated hardware performance allows for a determination of the DESI footprint and the number of times DESI has covered it at sub-arcsecond level precision. This enables the completeness of any DESI sample to be modeled at this same resolution. The pipeline developed to create LSS catalogs has been designed to easily allow robustness tests and enable future improvements. We describe how it allows ongoing work improving the match between galaxy and random catalogs, such as including further information when assigning redshifts to randoms, accounting for fluctuations in target density, accounting for variation in the redshift success rate, and accommodating blinding schemes., Comment: Accepted (by JCAP) version of supporting publication of DESI 2024II: Sample definitions, characteristics, and two-point clustering statistics

In anticipation of forthcoming data releases of current and future spectroscopic surveys, we present the validation tests and analysis of systematic effects within \texttt{velocileptors} modeling pipeline when fitting mock data from the \texttt{AbacusSummit} N-body simulations. We compare the constraints obtained from parameter compression methods to the direct fitting (Full-Modeling) approaches of modeling the galaxy power spectra, and show that the ShapeFit extension to the traditional template method is consistent with the Full-Modeling method within the standard $\Lambda$CDM parameter space. We show the dependence on scale cuts when fitting the different redshift bins using the ShapeFit and Full-Modeling methods. We test the ability to jointly fit data from multiple redshift bins as well as joint analysis of the pre-reconstruction power spectrum with the post-reconstruction BAO correlation function signal. We further demonstrate the behavior of the model when opening up the parameter space beyond $\Lambda$CDM and also when combining likelihoods with external datasets, namely the Planck CMB priors. Finally, we describe different parametrization options for the galaxy bias, counterterm, and stochastic parameters, and employ the halo model in order to physically motivate suitable priors that are necessary to ensure the stability of the perturbation theory., Comment: 56 pages, 23 figures. Supporting publication of DESI 2024 V: Analysis of the full shape of two-point clustering statistics from galaxies and quasars

In the era of precision cosmology, ensuring the integrity of data analysis through blinding techniques is paramount -- a challenge particularly relevant for the Dark Energy Spectroscopic Instrument (DESI). DESI represents a monumental effort to map the cosmic web, with the goal to measure the redshifts of tens of millions of galaxies and quasars. Given the data volume and the impact of the findings, the potential for confirmation bias poses a significant challenge. To address this, we implement and validate a comprehensive blind analysis strategy for DESI Data Release 1 (DR1), tailored to the specific observables DESI is most sensitive to: Baryonic Acoustic Oscillations (BAO), Redshift-Space Distortion (RSD) and primordial non-Gaussianities (PNG). We carry out the blinding at the catalog level, implementing shifts in the redshifts of the observed galaxies to blind for BAO and RSD signals and weights to blind for PNG through a scale-dependent bias. We validate the blinding technique on mocks, as well as on data by applying a second blinding layer to perform a battery of sanity checks. We find that the blinding strategy alters the data vector in a controlled way such that the BAO and RSD analysis choices do not need any modification before and after unblinding. The successful validation of the blinding strategy paves the way for the unblinded DESI DR1 analysis, alongside future blind analyses with DESI and other surveys., Comment: Supporting publication of "DESI 2024 II: Sample definitions, characteristics, and two-point clustering statistics", "DESI 2024 III: Baryon Acoustic Oscillations from Galaxies and Quasars", and "DESI 2024 V: Analysis of the full shape of two-point clustering statistics from galaxies and quasars". (v2 - update DESI references)

In preparation for the next generation of galaxy redshift surveys, and in particular the year-one data release from the Dark Energy Spectroscopic Instrument (DESI), we investigate the consistency of a variety of effective field theory models that describe the galaxy-galaxy power spectra in redshift space into the quasi-linear regime using 1-loop perturbation theory. These models are employed in the pipelines \texttt{velocileptors}, \texttt{PyBird}, and \texttt{Folps$\nu$}. While these models have been validated independently, a detailed comparison with consistent choices has not been attempted. After briefly discussing the theoretical differences between the models we describe how to provide a more apples-to-apples comparison between them. We present the results of fitting mock spectra from the \texttt{AbacusSummit} suite of N-body simulations provided in three redshift bins to mimic the types of dark time tracers targeted by the DESI survey. We show that the theories behave similarly and give consistent constraints in both the forward-modeling and ShapeFit compressed fitting approaches. We additionally generate (noiseless) synthetic data from each pipeline to be fit by the others, varying the scale cuts in order to show that the models agree within the range of scales for which we expect 1-loop perturbation theory to be applicable. This work lays the foundation of Full-Shape analysis with DESI Y1 galaxy samples where in the tests we performed, we found no systematic error associated with the modeling of the galaxy redshift space power spectrum for this volume., Comment: 33 pages, 12 figures. Supporting publication of DESI 2024 V: Analysis of the full shape of two-point clustering statistics from galaxies and quasars

The Dark Energy Spectroscopic Instrument (DESI) will provide unprecedented information about the large-scale structure of our Universe. In this work, we study the robustness of the theoretical modelling of the power spectrum of FOLPS, a novel effective field theory-based package for evaluating the redshift space power spectrum in the presence of massive neutrinos. We perform this validation by fitting the AbacusSummit high-accuracy $N$-body simulations for Luminous Red Galaxies, Emission Line Galaxies and Quasar tracers, calibrated to describe DESI observations. We quantify the potential systematic error budget of FOLPS, finding that the modelling errors are fully sub-dominant for the DESI statistical precision within the studied range of scales. Additionally, we study two complementary approaches to fit and analyse the power spectrum data, one based on direct Full-Modelling fits and the other on the ShapeFit compression variables, both resulting in very good agreement in precision and accuracy. In each of these approaches, we study a set of potential systematic errors induced by several assumptions, such as the choice of template cosmology, the effect of prior choice in the nuisance parameters of the model, or the range of scales used in the analysis. Furthermore, we show how opening up the parameter space beyond the vanilla $\Lambda$CDM model affects the DESI observables. These studies include the addition of massive neutrinos, spatial curvature, and dark energy equation of state. We also examine how relaxing the usual Cosmic Microwave Background and Big Bang Nucleosynthesis priors on the primordial spectral index and the baryonic matter abundance, respectively, impacts the inference on the rest of the parameters of interest. This paper pathways towards performing a robust and reliable analysis of the shape of the power spectrum of DESI galaxy and quasar clustering using FOLPS., Comment: Supporting publication of DESI 2024 VII: Cosmological constraints from full-shape analyses of the two-point clustering statistics measurements, in preparation (2024)

In the contemporary era of high-precision spectroscopic surveys, led by projects like DESI, there is an increasing demand for optimizing the extraction of cosmological information from clustering data. This work conducts a thorough comparison of various methodologies for modeling the full shape of the two-point statistics in configuration space. We investigate the performance of both direct fits (Full-Modeling) and the parameter compression approaches (ShapeFit and Standard). We utilize the ABACUS-SUMMIT simulations, tailored to exceed DESI's precision requirements. Particularly, we fit the two-point statistics of three distinct tracers (LRG, ELG, and QSO), by employing a Gaussian Streaming Model in tandem with Convolution Lagrangian Perturbation Theory and Effective Field Theory. We explore methodological setup variations, including the range of scales, the set of galaxy bias parameters, the inclusion of the hexadecapole, as well as model extensions encompassing varying $n_s$ and allowing for $w_0w_a$CDM dark energy model. Throughout these varied explorations, while precision levels fluctuate and certain configurations exhibit tighter parameter constraints, our pipeline consistently recovers the parameter values of the mocks within $1\sigma$ in all cases for a 1-year DESI volume. Additionally, we compare the performance of configuration space analysis with its Fourier space counterpart using three models: PyBird, FOLPS and velocileptors, presented in companion papers. We find good agreement with the results from all these models., Comment: Supporting publication of DESI 2024 KP5

The Dark Energy Spectroscopic Instrument (DESI) will provide precise measurements of Baryon Acoustic Oscillations (BAO) to constrain the expansion history of the Universe and set stringent constraints on dark energy. Therefore, precise control of the global error budget due to various systematic effects is required for the DESI 2024 BAO analysis. In this work, we focus on the robustness of the BAO analysis against the Halo Occupation Distribution (HOD) modeling for the Emission Line Galaxy (ELG) tracer. Based on a common dark matter simulation, our analysis relies on HOD mocks tuned to early DESI data, namely the One-Percent survey data. To build the mocks, we use several HOD models for the ELG tracer as well as extensions to the baseline HOD models. Among these extensions, we consider distinct recipes for galactic conformity and assembly bias. We perform two independent analyses in the Fourier space and in the configuration space. We recover the BAO signal from two-point measurements after performing reconstruction on our mocks. Additionally, we also apply the control variates technique to reduce sample variance noise. Our BAO analysis can recover the isotropic BAO parameter $\alpha_\text{iso}$ within 0.1\% and the Alcock Paczynski parameter $\alpha_\text{AP}$ within 0.3\%. Overall, we find that our systematic error due to the HOD dependence is below 0.17\%, with the Fourier space analysis being more robust against the HOD systematics. We conclude that our analysis pipeline is robust enough against the HOD systematics for the ELG tracer in the DESI 2024 BAO analysis., Comment: Supporting publication of DESI 2024 III: Baryon Acoustic Oscillations from Galaxies and Quasars

In this paper, we present the estimation of systematics related to the halo occupation distribution (HOD) modeling in the baryon acoustic oscillations (BAO) distance measurement of the Dark Energy Spectroscopic Instrument (DESI) 2024 analysis. This paper focuses on the study of HOD systematics for luminous red galaxies (LRG). We consider three different HOD models for LRGs, including the base 5-parameter vanilla model and two extensions to it, that we refer to as baseline and extended models. The baseline model is described by the 5 vanilla HOD parameters, an incompleteness factor and a velocity bias parameter, whereas the extended one also includes a galaxy assembly bias and a satellite profile parameter. We utilize the 25 dark matter simulations available in the AbacusSummit simulation suite at $z=$ 0.8 and generate mock catalogs for our different HOD models. To test the impact of the HOD modeling in the position of the BAO peak, we run BAO fits for all these sets of simulations and compare the best-fit BAO-scaling parameters $\alpha_{\rm iso}$ and $\alpha_{\rm AP}$ between every pair of HOD models. We do this for both Fourier and configuration spaces independently, using post-reconstruction measurements. We find a 3.3$\sigma$ detection of HOD systematic for $\alpha_{\rm AP}$ in configuration space with an amplitude of 0.19%. For the other cases, we did not find a 3$\sigma$ detection, and we decided to compute a conservative estimation of the systematic using the ensemble of shifts between all pairs of HOD models. By doing this, we quote a systematic with an amplitude of 0.07% in $\alpha_{\rm iso}$ for both Fourier and configuration spaces; and of 0.09% in $\alpha_{\rm AP}$ for Fourier space., Comment: 36 pages, 9 figures. Supporting publication of DESI 2024 III: Baryon Acoustic Oscillations from Galaxies and Quasars

We present an optimized way of producing the fast semi-analytical covariance matrices for the Legendre moments of the two-point correlation function, taking into account survey geometry and mimicking the non-Gaussian effects. We validate the approach on simulated (mock) catalogs for different galaxy types, representative of the Dark Energy Spectroscopic Instrument (DESI) Data Release 1, used in 2024 analyses. We find only a few percent differences between the mock sample covariance matrix and our results, which can be expected given the approximate nature of the mocks, although we do identify discrepancies between the shot-noise properties of the DESI fiber assignment algorithm and the faster approximation used in the mocks. Importantly, we find a close agreement (<~ 5% relative differences) in the projected errorbars for distance scale parameters for the baryon acoustic oscillation measurements. This confirms our method as an attractive alternative to simulation-based covariance matrices, especially for non-standard models or galaxy sample selections, in particular, relevant to the broad current and future analyses of DESI data., Comment: Supporting publication of DESI 2024 III: Baryon Acoustic Oscillations from Galaxies and Quasars (arXiv:2404.03000). 29 pages, 4 figures. Prepared for submission to JCAP. Code available at https://github.com/oliverphilcox/RascalC and https://github.com/misharash/RascalC-scripts/tree/DESI2024. Data points from the plots available at https://zenodo.org/doi/10.5281/zenodo.10895161

A critical requirement of spectroscopic large scale structure analyses is correcting for selection of which galaxies to observe from an isotropic target list. This selection is often limited by the hardware used to perform the survey which will impose angular constraints of simultaneously observable targets, requiring multiple passes to observe all of them. In SDSS this manifested solely as the collision of physical fibers and plugs placed in plates. In DESI, there is the additional constraint of the robotic positioner which controls each fiber being limited to a finite patrol radius. A number of approximate methods have previously been proposed to correct the galaxy clustering statistics for these effects, but these generally fail on small scales. To accurately correct the clustering we need to upweight pairs of galaxies based on the inverse probability that those pairs would be observed (Bianchi \& Percival 2017). This paper details an implementation of that method to correct the Dark Energy Spectroscopic Instrument (DESI) survey for incompleteness. To calculate the required probabilities, we need a set of alternate realizations of DESI where we vary the relative priority of otherwise identical targets. These realizations take the form of alternate Merged Target Ledgers (AMTL), the files that link DESI observations and targets. We present the method used to generate these alternate realizations and how they are tracked forward in time using the real observational record and hardware status, propagating the survey as though the alternate orderings had been adopted. We detail the first applications of this method to the DESI One-Percent Survey (SV3) and the DESI year 1 data. We include evaluations of the pipeline outputs, estimation of survey completeness from this and other methods, and validation of the method using mock galaxy catalogs., Comment: 30 pages, 21 figures

We present cosmological results from the measurement of baryon acoustic oscillations (BAO) in galaxy, quasar and Lyman-$\alpha$ forest tracers from the first year of observations from the Dark Energy Spectroscopic Instrument (DESI), to be released in the DESI Data Release 1. DESI BAO provide robust measurements of the transverse comoving distance and Hubble rate, or their combination, relative to the sound horizon, in seven redshift bins from over 6 million extragalactic objects in the redshift range $0.1-1$ and $w_a<0$. This preference is 2.6$\sigma$ for the DESI+CMB combination, and persists or grows when SN~Ia are added in, giving results discrepant with the $\Lambda$CDM model at the $2.5\sigma$, $3.5\sigma$ or $3.9\sigma$ levels for the addition of Pantheon+, Union3, or DES-SN5YR datasets respectively. For the flat $\Lambda$CDM model with the sum of neutrino mass $\sum m_\nu$ free, combining the DESI and CMB data yields an upper limit $\sum m_\nu < 0.072$ $(0.113)$ eV at 95% confidence for a $\sum m_\nu>0$ $(\sum m_\nu>0.059)$ eV prior. These neutrino-mass constraints are substantially relaxed in models beyond $\Lambda$CDM. [Abridged.], Comment: This DESI Collaboration Key Publication is part of the 2024 publication series using the first year of observations (see https://data.desi.lbl.gov/doc/papers). Typos corrected and a new figure and discussion added to Appendix A

We present the measurement of Baryon Acoustic Oscillations (BAO) from the Lyman-$\alpha$ (Ly$\alpha$) forest of high-redshift quasars with the first-year dataset of the Dark Energy Spectroscopic Instrument (DESI). Our analysis uses over $420\,000$ Ly$\alpha$ forest spectra and their correlation with the spatial distribution of more than $700\,000$ quasars. An essential facet of this work is the development of a new analysis methodology on a blinded dataset. We conducted rigorous tests using synthetic data to ensure the reliability of our methodology and findings before unblinding. Additionally, we conducted multiple data splits to assess the consistency of the results and scrutinized various analysis approaches to confirm their robustness. For a given value of the sound horizon ($r_d$), we measure the expansion at $z_{\rm eff}=2.33$ with 2\% precision, $H(z_{\rm eff}) = (239.2 \pm 4.8) (147.09~{\rm Mpc} /r_d)$ km/s/Mpc. Similarly, we present a 2.4\% measurement of the transverse comoving distance to the same redshift, $D_M(z_{\rm eff}) = (5.84 \pm 0.14) (r_d/147.09~{\rm Mpc})$ Gpc. Together with other DESI BAO measurements at lower redshifts, these results are used in a companion paper to constrain cosmological parameters., Comment: This DESI Collaboration Key Publication is part of the 2024 publication series using the first year of observations (see https://data.desi.lbl.gov/doc/papers). Minor changes in v4, version accepted for publication in JCAP

Baryon acoustic oscillations (BAO) provide a robust standard ruler to measure the expansion history of the Universe through galaxy clustering. Density-field reconstruction is now a widely adopted procedure for increasing the precision and accuracy of the BAO detection. With the goal of finding the optimal reconstruction settings to be used in the DESI 2024 galaxy BAO analysis, we assess the sensitivity of the post-reconstruction BAO constraints to different choices in our analysis configuration, performing tests on blinded data from the first year of DESI observations (DR1), as well as on mocks that mimic the expected clustering and selection properties of the DESI DR1 target samples. Overall, we find that BAO constraints remain robust against multiple aspects in the reconstruction process, including the choice of smoothing scale, treatment of redshift-space distortions, fiber assignment incompleteness, and parameterizations of the BAO model. We also present a series of tests that DESI followed in order to assess the maturity of the end-to-end galaxy BAO pipeline before the unblinding of the large-scale structure catalogs., Comment: Supporting publication of DESI 2024 III: Baryon Acoustic Oscillations from Galaxies and Quasars

We present the DESI 2024 galaxy and quasar baryon acoustic oscillations (BAO) measurements using over 5.7 million unique galaxy and quasar redshifts in the range 0.1

Surveys of cosmological large-scale structure (LSS) are sensitive to the presence of local primordial non-Gaussianity (PNG), and may be used to constrain models of inflation. Local PNG, characterized by fNL, the amplitude of the quadratic correction to the potential of a Gaussian random field, is traditionally measured from LSS two-point and three-point clustering via the power spectrum and bi-spectrum. We propose a framework to measure fNL using the configuration space two-point correlation function (2pcf) monopole and three-point correlation function (3pcf) monopole of survey tracers. Our model estimates the effect of the scale-dependent bias induced by the presence of PNG on the 2pcf and 3pcf from the clustering of simulated dark matter halos. We describe how this effect may be scaled to an arbitrary tracer of the cosmological matter density. The 2pcf and 3pcf of this tracer are measured to constrain the value of fNL. Using simulations of luminous red galaxies observed by the Dark Energy Spectroscopic Instrument (DESI), we demonstrate the accuracy and constraining power of our model, and forecast the ability to constrainfNL to a precision of sigma(fNL) = 22 with one year of DESI survey data.

This paper provides a comprehensive overview of how fitting of Baryon Acoustic Oscillations (BAO) is carried out within the upcoming Dark Energy Spectroscopic Instrument's (DESI) 2024 results using its DR1 dataset, and the associated systematic error budget from theory and modelling of the BAO. We derive new results showing how non-linearities in the clustering of galaxies can cause potential biases in measurements of the isotropic ($\alpha_{\mathrm{iso}}$) and anisotropic ($\alpha_{\mathrm{ap}}$) BAO distance scales, and how these can be effectively removed with an appropriate choice of reconstruction algorithm. We then demonstrate how theory leads to a clear choice for how to model the BAO and develop, implement and validate a new model for the remaining smooth-broadband (i.e., without BAO) component of the galaxy clustering. Finally, we explore the impact of all remaining modelling choices on the BAO constraints from DESI using a suite of high-precision simulations, arriving at a set of best-practices for DESI BAO fits, and an associated theory and modelling systematic error. Overall, our results demonstrate the remarkable robustness of the BAO to all our modelling choices and motivate a combined theory and modelling systematic error contribution to the post-reconstruction DESI BAO measurements of no more than $0.1\%$ ($0.2\%$) for its isotropic (anisotropic) distance measurements. We expect the theory and best-practices laid out to here to be applicable to other BAO experiments in the era of DESI and beyond., Comment: 30 pages, 18 figures, 1 table, updated to match version accepted by MNRAS

Accurate mock galaxy catalogues are crucial to validate analysis pipelines used to constrain dark energy models. We present a fast HOD-fitting method which we apply to the AbacusSummit simulations to create a set of mock catalogues for the DESI Bright Galaxy Survey, which contain r-band magnitudes and g-r colours. The halo tabulation method fits HODs for different absolute magnitude threshold samples simultaneously, preventing unphysical HOD crossing between samples. We validate the HOD fitting procedure by fitting to real-space clustering measurements and galaxy number densities from the MXXL BGS mock, which was tuned to the SDSS and GAMA surveys. The best-fitting clustering measurements and number densities are mostly within the assumed errors, but the clustering for the faint samples is low on large scales. The best-fitting HOD parameters are robust when fitting to simulations with different realisations of the initial conditions. When varying the cosmology, trends are seen as a function of each cosmological parameter. We use the best-fitting HOD parameters to create cubic box and cut sky mocks from the AbacusSummit simulations, in a range of cosmologies. As an illustration, we compare the Mr<-20 sample of galaxies in the mock with BGS measurements from the DESI one-percent survey. We find good agreement in the number densities, and the projected correlation function is reasonable, with differences that can be improved in the future by fitting directly to BGS clustering measurements. The cubic box and cut-sky mocks in different cosmologies are made publicly available., Comment: 17 pages, 9 figures, accepted for publication in MNRAS

We present initial results from the Dark Energy Spectroscopic Instrument (DESI) Complete Calibration of the Color-Redshift Relation (DC3R2) secondary target survey. Our analysis uses 230k galaxies that overlap with KiDS-VIKING $ugriZYJHK_s$ photometry to calibrate the color-redshift relation and to inform photometric redshift (photo-z) inference methods of future weak lensing surveys. Together with Emission Line Galaxies (ELGs), Luminous Red Galaxies (LRGs), and the Bright Galaxy Survey (BGS) that provide samples of complementary color, the DC3R2 targets help DESI to span 56% of the color space visible to Euclid and LSST with high confidence spectroscopic redshifts. The effects of spectroscopic completeness and quality are explored, as well as systematic uncertainties introduced with the use of common Self Organizing Maps trained on different photometry than the analysis sample. We further examine the dependence of redshift on magnitude at fixed color, important for the use of bright galaxy spectra to calibrate redshifts in a fainter photometric galaxy sample. We find that noise in the KiDS-VIKING photometry introduces a dominant, apparent magnitude dependence of redshift at fixed color, which indicates a need for carefully chosen deep drilling fields, and survey simulation to model this effect for future weak lensing surveys., Comment: 19 pages, 16 figures, published in MNRAS, interactive visualizations at https://jmccull.github.io/DC3R2_Overview

We present results from a set of mock lightcones for the DESI One-Percent Survey, created from the Uchuu simulation. This This 8 (Gpc/h)^3 N-body simulation comprises 2.1 trillion particles and provides high-resolution dark matter (sub)haloes in the framework of the Planck base-LCDM cosmology. Employing the subhalo abundance matching (SHAM) technique, we populate the Uchuu (sub)haloes with all four DESI tracers (BGS, LRG, ELG and QSO) to z = 2.1. Our method accounts for redshift evolution as well as the clustering dependence on luminosity and stellar mass. The two-point clustering statistics of the DESI One-Percent Survey generally agree with predictions from Uchuu across scales ranging from 0.3 Mpc/h to 100 Mpc/h for the BGS and across scales ranging from 5 Mpc/h to 100 Mpc/h for the other tracers. We observe some differences in clustering statistics that can be attributed to incompleteness of the massive end of the stellar mass function of LRGs, our use of a simplified galaxy-halo connection model for ELGs and QSOs, and cosmic variance. We find that at the high precision of Uchuu, the shape of the halo occupation distribution (HOD) of the BGS and LRG samples are not fully captured by the standard 5-parameter HOD model. However, the ELGs and QSOs show agreement with an adopted Gaussian distribution for central haloes with a power law for satellites. We observe fair agreement in the large-scale bias measurements between data and mock samples, although the BGS data exhibits smaller bias values, likely due to cosmic variance. The bias dependence on absolute magnitude, stellar mass and redshift aligns with that of previous surveys. These results provide DESI with tools to generate high-fidelity lightcones for the remainder of the survey and enhance our understanding of the galaxy-halo connection., Comment: 24 pages, 16 figures, 5 tables, accepted for publication in A&A. The Uchuu-DESI lightcones are available at https://data.desi.lbl.gov

The Dark Energy Spectroscopic Instrument (DESI) completed its five-month Survey Validation in May 2021. Spectra of stellar and extragalactic targets from Survey Validation constitute the first major data sample from the DESI survey. This paper describes the public release of those spectra, the catalogs of derived properties, and the intermediate data products. In total, the public release includes good-quality spectral information from 466,447 objects targeted as part of the Milky Way Survey, 428,758 as part of the Bright Galaxy Survey, 227,318 as part of the Luminous Red Galaxy sample, 437,664 as part of the Emission Line Galaxy sample, and 76,079 as part of the Quasar sample. In addition, the release includes spectral information from 137,148 objects that expand the scope beyond the primary samples as part of a series of secondary programs. Here, we describe the spectral data, data quality, data products, Large-Scale Structure science catalogs, access to the data, and references that provide relevant background to using these spectra., Comment: 43 pages, 7 figures, 17 tables, accepted for publication in the Astronomical Journal

The Dark Energy Spectroscopic Instrument (DESI) was designed to conduct a survey covering 14,000 deg$^2$ over five years to constrain the cosmic expansion history through precise measurements of Baryon Acoustic Oscillations (BAO). The scientific program for DESI was evaluated during a five month Survey Validation (SV) campaign before beginning full operations. This program produced deep spectra of tens of thousands of objects from each of the stellar (MWS), bright galaxy (BGS), luminous red galaxy (LRG), emission line galaxy (ELG), and quasar target classes. These SV spectra were used to optimize redshift distributions, characterize exposure times, determine calibration procedures, and assess observational overheads for the five-year program. In this paper, we present the final target selection algorithms, redshift distributions, and projected cosmology constraints resulting from those studies. We also present a `One-Percent survey' conducted at the conclusion of Survey Validation covering 140 deg$^2$ using the final target selection algorithms with exposures of a depth typical of the main survey. The Survey Validation indicates that DESI will be able to complete the full 14,000 deg$^2$ program with spectroscopically-confirmed targets from the MWS, BGS, LRG, ELG, and quasar programs with total sample sizes of 7.2, 13.8, 7.46, 15.7, and 2.87 million, respectively. These samples will allow exploration of the Milky Way halo, clustering on all scales, and BAO measurements with a statistical precision of 0.28% over the redshift interval $z<1.1$, 0.39% over the redshift interval $1.1

The Dark Energy Spectroscopic Instrument (DESI) Survey has obtained a set of spectroscopic measurements of galaxies to validate the final survey design and target selections. To assist in these tasks, we visually inspect (VI) DESI spectra of approximately 2,500 bright galaxies, 3,500 luminous red galaxies (LRGs), and 10,000 emission line galaxies (ELGs), to obtain robust redshift identifications. We then utilize the VI redshift information to characterize the performance of the DESI operation. Based on the VI catalogs, our results show that the final survey design yields samples of bright galaxies, LRGs, and ELGs with purity greater than $99\%$. Moreover, we demonstrate that the precision of the redshift measurements is approximately 10 km/s for bright galaxies and ELGs and approximately 40 km/s for LRGs. The average redshift accuracy is within 10 km/s for the three types of galaxies. The VI process also helps improve the quality of the DESI data by identifying spurious spectral features introduced by the pipeline. Finally, we show examples of unexpected real astronomical objects, such as Ly$\alpha$ emitters and strong lensing candidates, identified by VI. These results demonstrate the importance and utility of visually inspecting data from incoming and upcoming surveys, especially during their early operation phases., Comment: 22 pages, 14 figures, 3 tables, one of a suite of 8 papers detailing targeting for DESI. ApJ accepted version with minor textual updates

The Dark Energy Spectroscopic Instrument (DESI) has embarked on an ambitious five-year survey to explore the nature of dark energy with spectroscopy of 40 million galaxies and quasars. DESI will determine precise redshifts and employ the Baryon Acoustic Oscillation method to measure distances from the nearby universe to z > 3.5, as well as measure the growth of structure and probe potential modifications to general relativity. In this paper we describe the significant instrumentation we developed for the DESI survey. The new instrumentation includes a wide-field, 3.2-deg diameter prime-focus corrector that focuses the light onto 5020 robotic fiber positioners on the 0.812 m diameter, aspheric focal surface. The positioners and their fibers are divided among ten wedge-shaped petals. Each petal is connected to one of ten spectrographs via a contiguous, high-efficiency, nearly 50 m fiber cable bundle. The ten spectrographs each use a pair of dichroics to split the light into three channels that together record the light from 360 - 980 nm with a resolution of 2000 to 5000. We describe the science requirements, technical requirements on the instrumentation, and management of the project. DESI was installed at the 4-m Mayall telescope at Kitt Peak, and we also describe the facility upgrades to prepare for DESI and the installation and functional verification process. DESI has achieved all of its performance goals, and the DESI survey began in May 2021. Some performance highlights include RMS positioner accuracy better than 0.1", SNR per \sqrt{\AA} > 0.5 for a z > 2 quasar with flux 0.28e-17 erg/s/cm^2/A at 380 nm in 4000s, and median SNR = 7 of the [OII] doublet at 8e-17 erg/s/cm^2 in a 1000s exposure for emission line galaxies at z = 1.4 - 1.6. We conclude with highlights from the on-sky validation and commissioning of the instrument, key successes, and lessons learned. (abridged), Comment: 78 pages, 32 figures, submitted to AJ

We report results of a study of Planck Sunyaev-Zel'dovich effect (SZE) selected galaxy cluster candidates using the Panoramic Survey Telescope & Rapid Response System (Pan-STARRS) imaging data. We first examine 150 Planck confirmed galaxy clusters with spectroscopic redshifts to test our algorithm for identifying optical counterparts and measuring their redshifts; our redshifts have a typical accuracy of $\sigma_{z/(1+z)} \sim 0.022$ for this sample. Using 60 random sky locations, we estimate that our chance of contamination through a random superposition is ~ 3 per cent. We then examine an additional 237 Planck galaxy cluster candidates that have no redshift in the source catalogue. Of these 237 unconfirmed cluster candidates we are able to confirm 60 galaxy clusters and measure their redshifts. A further 83 candidates are so heavily contaminated by stars due to their location near the Galactic plane that we do not attempt to identify counterparts. For the remaining 94 candidates we find no optical counterpart but use the depth of the Pan-STARRS1 data to estimate a redshift lower limit $z_{\text{lim}(10^{15})}$ beyond which we would not have expected to detect enough galaxies for confirmation. Scaling from the already published Planck sample, we expect that $\sim$12 of these unconfirmed candidates may be real clusters., Comment: 11 pages, 9 figures

The estimated stellar masses of galaxies are widely used to characterize how the galaxy population evolves over cosmic time. If stellar masses can be estimated in a robust manner, free from any bias, global diagnostics such as the stellar mass function can be used to constrain the physics of galaxy formation. We explore how galaxy stellar masses, estimated by fitting broad-band spectral energy distributions (SEDs) with stellar population models, can be biased as a result of commonly adopted assumptions for the star-formation and chemical enrichment histories, recycled fractions and dust attenuation curves of galaxies. We apply the observational technique of broad-band SED fitting to model galaxy SEDs calculated by the theoretical galaxy formation model GALFORM, isolating the effect of each of these assumptions. We find that, averaged over the entire galaxy population, the common assumption of exponentially declining star-formation histories does not adversely affect stellar mass estimation. We show that fixing the metallicity in SED fitting or using sparsely sampled metallicity grids can introduce mass dependent systematics into stellar mass estimates. We find that the common assumption of a star-dust geometry corresponding to a uniform foreground dust screen can cause the stellar masses of dusty model galaxies to be significantly underestimated. Finally, we show that stellar mass functions recovered by applying SED fitting to model galaxies at high redshift can differ significantly in both shape and normalization from the intrinsic mass functions predicted by a given model. Given these differences, our methodology of using stellar masses estimated from model galaxy SEDs offers a new, self-consistent way to compare model predictions with observations., Comment: 29 pages, 16 Figures, changed to match published MNRAS version

The Galaxy And Mass Assembly (GAMA) survey is a multiwavelength photometric and spectroscopic survey, using the AAOmega spectrograph on the Anglo-Australian Telescope to obtain spectra for up to ~300000 galaxies over 280 square degrees, to a limiting magnitude of r_pet < 19.8 mag. The target galaxies are distributed over 0

We apply a recently developed scaling technique to the Millennium-XXL, one of the largest cosmological N-body simulations carried out to date 3x10^11 particles within a cube of volume ~70Gpc^3). This allows us to investigate the cosmological parameter dependence of the mass and evolution of haloes in the extreme high-mass tail of the z=6 distribution. We assume these objects to be likely hosts for the population of rare but ultraluminous high-redshift quasars discovered by the Sloan Digital Sky Survey. Haloes with a similar abundance to these quasars have a median mass of 9x10^12 Msun in the currently preferred cosmology, but do not evolve into equally extreme objects at z=0. Rather, their descendants span the full range conventionally assigned to present-day clusters, 6x10^13 to 2.5x10^15 Msun for this same cosmology. The masses both at z=6 and at z=0 shift up or down by factors exceeding two if cosmological parameters are pushed to the boundaries of the range discussed in published interpretations of data from the WMAP satellite. The main factor determining the future growth of a high-mass z=6 halo is the mean overdensity of its environment on scales of 7 to 14 Mpc, and descendant masses can be predicted 6 to 8 times more accurately if this density is known than if it is not. All these features are not unique to extreme high-z haloes, but are generic to hierarchical growth. Finally, we find that extreme haloes at z=6 typically acquired about half of their total mass in the preceding 100 Myr, implying very large recent accretion rates which may be related to the large black hole masses and high luminosities of the SDSS quasars., Comment: 10 pages, 6 figures. Replaced with version published in MNRAS

The formation of galaxies is regulated by a balance between the supply of gas and the rate at which it is ejected. Traditional explanations of gas ejection equate the energy required to escape the galaxy or host halo to an estimate for the energy yield from supernovae. This yield is usually assumed to be a constant fraction of the total available from the supernova, or is derived from the assumption of a consistent momentum yield. By applying these ideas in the context of a cold dark matter cosmogony, we derive a 1st-order analytic connection between these working assumptions and the expected relationship between baryon content and galaxy circular velocity, and find that these quick predictions straddle recent observational estimates. To examine the premises behind these theories in more detail, we then explore their applicability to a set of gasdynamical simulations of idealised galaxies. We show that different premises dominate to differing degrees in the simulated outflow, depending on the mass of the system and the resolution with which it is simulated. Using this study to anticipate the emergent behaviour at arbitrarily high resolution, we motivate more comprehensive analytic model which allows for the range of velocities with which the gas may exit the system, and incorporates both momentum and energy-based constraints on the outflow. Using a trial exit velocity distribution, this is shown to be compatible with the observed baryon fractions in intermediate-mass systems, but implies that current estimates for low-mass systems can not be solely accounted for by supernova winds under commonly-held assumptions., Comment: 16 pages, 13 figures. Accepted to MNRAS

Star-forming galaxies which are too faint to be detected individually produce intensity fluctuations in the cosmic background light. This contribution needs to be taken into account as a foreground when using the primordial signal to constrain cosmological parameters. The extragalactic fluctuations are also interesting in their own right as they depend on the star formation history of the Universe and the way in which this connects with the formation of cosmic structure. We present a new framework which allows us to predict the occupation of dark matter haloes by star-forming galaxies and uses this information, in conjunction with an N-body simulation of structure formation, to predict the power spectrum of intensity fluctuations in the infrared background. We compute the emission from galaxies at far-infrared, millimetre and radio wavelengths. Our method gives accurate predictions for the clustering of galaxies both for the one halo and two halo terms. We illustrate our new framework using a previously published model which reproduces the number counts and redshift distribution of galaxies selected by their emission at $850\,\mu$m. Without adjusting any of the model parameters, the predictions show encouraging agreement at high frequencies and on small angular scales with recent estimates of the extragalactic fluctuations in the background made from early data analysed by the Planck Collaboration. There are, however, substantial discrepancies between the model predictions and observations on large angular scales and at low frequencies, which illustrates the usefulness of the intensity fluctuations as a constraint on galaxy formation models., Comment: 16 pages, 14 figures, Accepted version for MNRAS

We use a coupled model of the formation and evolution of galaxies and black holes (BH) to study the evolution of active galactic nuclei (AGN) in a cold dark matter universe. The model predicts the BH mass, spin and mass accretion history. BH mass grows via accretion triggered by discs becoming dynamically unstable or galaxy mergers (called the starburst mode) and accretion from quasi-hydrostatic hot gas haloes (called the hot-halo mode). By taking into account AGN obscuration, we obtain a very good fit to the observed luminosity functions (LF) of AGN (optical, soft and hard X-ray, and bolometric) for a wide range of redshifts (0

Semi-analytic models are a powerful tool for studying the formation of galaxies. However, these models inevitably involve a significant number of poorly constrained parameters that must be adjusted to provide an acceptable match to the observed universe. In this paper, we set out to quantify the degree to which observational data-sets can constrain the model parameters. By revealing degeneracies in the parameter space we can hope to better understand the key physical processes probed by the data. We use novel mathematical techniques to explore the parameter space of the GALFORM semi-analytic model. We base our investigation on the Bower et al. 2006 version of GALFORM, adopting the same methodology of selecting model parameters based on an acceptable match to the local bJ and K luminosity functions. The model contains 16 parameters that are poorly constrained, and we investigate this parameter space using the Model Emulator technique, constructing a Bayesian approximation to the GALFORM model that can be rapidly evaluated at any point in parameter space. By combining successive waves of emulation, we show that only 0.26% of the initial volume is of interest for further exploration. However, within this region we show that the Bower et al. 2006 model is only one choice from an extended sub-space of model parameters that can provide equally acceptable fits. We explore the geometry of this region and begin to explore the physical connections between parameters that are exposed by this analysis. We also consider the impact of adding additional observational data to further constrain the parameter space., Comment: 33 pages, 15 figures. Accepted by MNRAS

The distribution of cold gas in dark matter haloes is driven by key processes in galaxy formation: gas cooling, galaxy mergers, star formation and reheating of gas by supernovae. We compare the predictions of four different galaxy formation models for the spatial distribution of cold gas. We find that satellite galaxies make little contribution to the abundance or clustering strength of cold gas selected samples, and are far less important than they are in optically selected samples. The halo occupation distribution function of present-day central galaxies with cold gas mass > 10^9 h^-1 Msun is peaked around a halo mass of ~ 10^11 h^-1 Msun, a scale that is set by the AGN suppression of gas cooling. The model predictions for the projected correlation function are in good agreement with measurements from the HI Parkes All-Sky Survey. We compare the effective volume of possible surveys with the Square Kilometre Array with those expected for a redshift survey in the near-infrared. Future redshift surveys using neutral hydrogen emission will be competitive with the most ambitious spectroscopic surveys planned in the near-infrared., Comment: 19 pages, 15 figures, To appear in MNRAS

We track the co-evolution of supermassive black holes (SMBHs) and their host galaxies. The calculation is embedded in the GALFORM semi-analytical model which simulates the formation and evolution of galaxies in a cold dark matter (CDM) universe. During the evolution of the host galaxy, hot and cold gas are added to the SMBH by flows triggered by halo gas cooling, disc instabilities and galaxy mergers. This builds up the mass and spin of the BH, and the resulting accretion power regulates the gas cooling and subsequent star formation. The accretion flow is assumed to form a geometrically thin cool disc when the accretion rate exceeds 0.01\dot{M}_Edd, and a geometrically thick, radiatively inefficient hot flow when the accretion rate falls below this value. The resulting quasar optical luminosity function matches observations very well, and the mass of the SMBH correlates with the mass of the galaxy bulge as observed. The BH spin distribution depends strongly on whether the gas in any given accretion episode remains in the same plane (prolonged accretion) or whether, due to self-gravity, it fragments into multiple, randomly aligned accretion episodes (chaotic accretion). In the chaotic accretion model there is a clear correlation of spin with SMBH mass. Massive BHs (M>5\times10^8\Msun) are hosted by giant elliptical galaxies and are rapidly spinning, while lower mass BHs are hosted in spiral galaxies and have much lower spin. Using the Blandford-Znajek mechanism for jet production to calculate the jet power, our model is able to reproduce the radio loudness of radio galaxies, LINERS and Seyferts. This is the first confirmation that a CDM galaxy formation model can reproduce the observed phenomenology of AGN., Comment: Accepted for publication in MNRAS after correcting for revisions suggested by the referee

The clustering amplitude of galaxies depends on their intrinsic luminosity. We compare the properties of publicly available galaxy formation models with clustering measurements from the two-degree field galaxy redshift survey. The model predictions show the same qualitative behaviour as the data but fail to match the observations at the level of accuracy at which current measurements can be made. We demonstrate that this is due to the model producing too many satellite galaxies in massive haloes. We implement simple models to describe two new processes, satellite-satellite mergers and the tidal dissolution of satellites to investigate their impact on the predicted clustering. We find that both processes need to be included in order to produce a model which matches the observations., Comment: 15 pages, 15 figures, submitted to MNRAS