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W. J. Percival

Publications and source records attributed to W. J. Percival.

At least 181 records · Page 10Linked to original sources

Euclid: Constraining linearly scale-independent modifications of gravity with the spectroscopic and photometric primary probes

The future Euclid space satellite mission will offer an invaluable opportunity to constrain modifications to Einstein's general relativity at cosmic scales. We focus on modified gravity models characterised, at linear scales, by a scale-independent growth of perturbations while featuring different testable types of derivative screening mechanisms at smaller non-linear scales. We considered three specific models, namely JBD, a scalar-tensor theory with a flat potential, the nDGP gravity, a braneworld model in which our Universe is a four-dimensional brane embedded in a five-dimensional Minkowski space-time, and $k$-mouflage (KM) gravity, an extension of $k$-essence scenarios with a universal coupling of the scalar field to matter. In preparation for real data, we provide forecasts from spectroscopic and photometric primary probes by Euclid on the cosmological parameters and the additional parameters of the models, respectively, $ω_{\rm BD}$, $Ω_{\rm rc}$ and $ε_{2,0}$. The forecast analysis employs the Fisher matrix method applied to weak lensing (WL); photometric galaxy clustering (GCph), spectroscopic galaxy clustering (GCsp) and the cross-correlation (XC) between GCph and WL. In an optimistic setting at 68.3\% confidence interval, we find the following percentage relative errors with Euclid alone: for $\log_{10}{ω_{\rm BD}}$, with a fiducial value of $ω_{\rm BD}=800$, 27.1\% using GCsp alone, 3.6\% using GCph+WL+XC and 3.2\% using GCph+WL+XC+GCsp; for $\log_{10}{Ω_{\rm rc}}$, with a fiducial value of $Ω_{\rm rc}=0.25$, we find 93.4\%, 20\% and 15\% respectively; and finally, for $ε_{2,0}=-0.04$, we find 3.4\%, 0.15\%, and 0.14\%. (abridged)

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Evaluating extensions to LCDM: an application of Bayesian model averaging and selection

We employ Bayesian Model Averaging (BMA) as a powerful statistical framework to address key cosmological questions about the universe's fundamental properties. We explore extensions beyond the standard $Λ$CDM model, considering a varying curvature density parameter $Ω_{\rm k}$, a spectral index $\mathrm{n}_{\rm s}=1$ and a varying $n_{\rm run}$, a constant dark energy equation of state (EOS) $w_0$CDM and a time-dependent one $w_0w_a$CDM. We also test cosmological data against a varying effective number of neutrino species $N_{\rm eff}$. Data from different combinations of cosmic microwave background (CMB) data from the last Planck PR4 analysis, CMB lensing from Planck 2018, baryonic acoustic oscillations (BAO) and the Bicep-KECK 2018 results, are used. We find that the standard $Λ$CDM model is favoured when combining CMB data with CMB lensing, BAO and Bicep-KECK 2018 data against $K-Λ$CDM model $N_{\rm eff}-Λ$CDM with a probability $> 80\%$. When investigating the dark energy EOS, we find that this dataset is not able to express a strong preference between the standard $Λ$CDM model and the constant dark energy EOS model $w_0$CDM, with an approximately split model posterior probability of $\approx 60\%:40\%$ in favour of $Λ$CDM, whereas the time-varying dark energy EOS model is ruled out. Finally, we find that the CMB data alone show a strong preference for a model that includes the running of the spectral index $n_{\rm run}$, with a probability $\approx 90\%$, when compared to the $n_{\rm s}=1$ model and the standard $Λ$CDM. Overall, we find that including the model uncertainty in the considered cases does not significantly impact the Hubble tension.

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Broad Absorption Line Quasars in the Dark Energy Spectroscopic Instrument Early Data Release

Broad absorption line (BAL) quasars are characterized by gas clouds that absorb flux at the wavelength of common quasar spectral features, although blueshifted by velocities that can exceed 0.1c. BAL features are interesting as signatures of significant feedback, yet they can also compromise cosmological studies with quasars by distorting the shape of the most prominent quasar emission lines, impacting redshift accuracy and measurements of the matter density distribution traced by the Lyman-alpha forest. We present a catalog of BAL quasars discovered in the Dark Energy Spectroscopic Instrument (DESI) survey Early Data Release, which were observed as part of DESI Survey Validation, as well as the first two months of the main survey. We describe our method to automatically identify BAL quasars in DESI data, the quantities we measure for each BAL, and investigate the completeness and purity of this method with mock DESI observations. We mask the wavelengths of the BAL features and re-evaluate each BAL quasar redshift, finding new redshifts which are 243 km/s smaller on average for the BAL quasar sample. These new, more accurate redshifts are important to obtain the best measurements of quasar clustering, especially at small scales. Finally, we present some spectra of rarer classes of BALs that illustrate the potential of DESI data to identify such populations for further study.

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Euclid preparation XLVI. The Near-IR Background Dipole Experiment with Euclid

Verifying the fully kinematic nature of the cosmic microwave background (CMB) dipole is of fundamental importance in cosmology. In the standard cosmological model with the Friedman-Lemaitre-Robertson-Walker (FLRW) metric from the inflationary expansion the CMB dipole should be entirely kinematic. Any non-kinematic CMB dipole component would thus reflect the preinflationary structure of spacetime probing the extent of the FLRW applicability. Cosmic backgrounds from galaxies after the matter-radiation decoupling, should have kinematic dipole component identical in velocity with the CMB kinematic dipole. Comparing the two can lead to isolating the CMB non-kinematic dipole. It was recently proposed that such measurement can be done using the near-IR cosmic infrared background (CIB) measured with the currently operating Euclid telescope, and later with Roman. The proposed method reconstructs the resolved CIB, the Integrated Galaxy Light (IGL), from Euclid's Wide Survey and probes its dipole, with a kinematic component amplified over that of the CMB by the Compton-Getting effect. The amplification coupled with the extensive galaxy samples forming the IGL would determine the CIB dipole with an overwhelming signal/noise, isolating its direction to sub-degree accuracy. We develop details of the method for Euclid's Wide Survey in 4 bands spanning 0.6 to 2 mic. We isolate the systematic and other uncertainties and present methodologies to minimize them, after confining the sample to the magnitude range with negligible IGL/CIB dipole from galaxy clustering. These include the required star-galaxy separation, accounting for the extinction correction dipole using the method newly developed here achieving total separation, accounting for the Earth's orbital motion and other systematic effects. (Abridged)

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DESI Complete Calibration of the Color-Redshift Relation (DC3R2): Results from early DESI data

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.

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A comparison of effective field theory models of redshift space galaxy power spectra for DESI 2024 and future surveys

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$ν$}. 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.

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Blinding scheme for the scale-dependence bias signature of local primordial non-Gaussianity for DESI 2024

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.

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DESI 2024: Constraints on Physics-Focused Aspects of Dark Energy using DESI DR1 BAO Data

Baryon acoustic oscillation data from the first year of the Dark Energy Spectroscopic Instrument (DESI) provide near percent-level precision of cosmic distances in seven bins over the redshift range $z=0.1$-$4.2$. We use this data, together with other distance probes, to constrain the cosmic expansion history using some well-motivated physical classes of dark energy. In particular, we explore three physics-focused behaviors of dark energy from the equation of state and energy density perspectives: the thawing class (matching many simple quintessence potentials), emergent class (where dark energy comes into being recently, as in phase transition models), and mirage class (where phenomenologically the distance to CMB last scattering is close to that from a cosmological constant $Λ$ despite dark energy dynamics). All three classes fit the data at least as well as $Λ$CDM, and indeed can improve on it by $Δχ^2\approx -5$ to $-17$ for the combination of DESI BAO with CMB and supernova data, while having one more parameter. The mirage class does essentially as well as $w_0w_a$CDM while having one less parameter. These classes of dynamical behaviors highlight worthwhile avenues for further exploration into the nature of dark energy.

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CMB lensing and Lyα forest cross bispectrum from DESI's first-year quasar sample

The squeezed cross-bispectrum \bispeconed\ between the gravitational lensing in the Cosmic Microwave Background and the 1D \lya\ forest power spectrum can constrain bias parameters and break degeneracies between $σ_8$ and other cosmological parameters. We detect \bispeconed\ with $4.8σ$ significance at an effective redshift $z_\mathrm{eff}=2.4$ using Planck PR3 lensing map and over 280,000 quasar spectra from the Dark Energy Spectroscopic Instrument's first-year data. We test our measurement against metal contamination and foregrounds such as Galactic extinction and clusters of galaxies by deprojecting the thermal Sunyaev-Zeldovich effect. We compare our results to a tree-level perturbation theory calculation and find reasonable agreement between the model and measurement.

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Euclid. V. The Flagship galaxy mock catalogue: a comprehensive simulation for the Euclid mission

We present the Flagship galaxy mock, a simulated catalogue of billions of galaxies designed to support the scientific exploitation of the Euclid mission. Euclid is a medium-class mission of the European Space Agency optimised to determine the properties of dark matter and dark energy on the largest scales of the Universe. It probes structure formation over more than 10 billion years primarily from the combination of weak gravitational lensing and galaxy clustering data. The breath of Euclid's data will also foster a wide variety of scientific analyses. The Flagship simulation was developed to provide a realistic approximation to the galaxies that will be observed by Euclid and used in its scientific analyses. We ran a state-of-the-art N-body simulation with four trillion particles, producing a lightcone on the fly. From the dark matter particles, we produced a catalogue of 16 billion haloes in one octant of the sky in the lightcone up to redshift z=3. We then populated these haloes with mock galaxies using a halo occupation distribution and abundance matching approach, calibrating the free parameters of the galaxy mock against observed correlations and other basic galaxy properties. Modelled galaxy properties include luminosity and flux in several bands, redshifts, positions and velocities, spectral energy distributions, shapes and sizes, stellar masses, star formation rates, metallicities, emission line fluxes, and lensing properties. We selected a final sample of 3.4 billion galaxies with a magnitude cut of H_E<26, where we are complete. We have performed a comprehensive set of validation tests to check the similarity to observational data and theoretical models. In particular, our catalogue is able to closely reproduce the main characteristics of the weak lensing and galaxy clustering samples to be used in the mission's main cosmological analysis. (abridged)

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Validation of the DESI 2024 Ly$α$ forest BAO analysis using synthetic datasets

The first year of data from the Dark Energy Spectroscopic Instrument (DESI) contains the largest set of Lyman-$α$ (Ly$α$) forest spectra ever observed. This data, collected in the DESI Data Release 1 (DR1) sample, has been used to measure the Baryon Acoustic Oscillation (BAO) feature at redshift $z=2.33$. In this work, we use a set of 150 synthetic realizations of DESI DR1 to validate the DESI 2024 Ly$α$ forest BAO measurement. The synthetic data sets are based on Gaussian random fields using the log-normal approximation. We produce realistic synthetic DESI spectra that include all major contaminants affecting the Ly$α$ forest. The synthetic data sets span a redshift range $1.8<z<3.8$, and are analysed using the same framework and pipeline used for the DESI 2024 Ly$α$ forest BAO measurement. To measure BAO, we use both the Ly$α$ auto-correlation and its cross-correlation with quasar positions. We use the mean of correlation functions from the set of DESI DR1 realizations to show that our model is able to recover unbiased measurements of the BAO position. We also fit each mock individually and study the population of BAO fits in order to validate BAO uncertainties and test our method for estimating the covariance matrix of the Ly$α$ forest correlation functions. Finally, we discuss the implications of our results and identify the needs for the next generation of Ly$α$ forest synthetic data sets, with the top priority being to simulate the effect of BAO broadening due to non-linear evolution.

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Euclid preparation. XXXIV. The effect of linear redshift-space distortions in photometric galaxy clustering and its cross-correlation with cosmic shear

The cosmological surveys that are planned for the current decade will provide us with unparalleled observations of the distribution of galaxies on cosmic scales, by means of which we can probe the underlying large-scale structure (LSS) of the Universe. This will allow us to test the concordance cosmological model and its extensions. However, precision pushes us to high levels of accuracy in the theoretical modelling of the LSS observables, so that no biases are introduced into the estimation of the cosmological parameters. In particular, effects such as redshift-space distortions (RSD) can become relevant in the computation of harmonic-space power spectra even for the clustering of the photometrically selected galaxies, as has previously been shown in literature. In this work, we investigate the contribution of linear RSD, as formulated in the Limber approximation by a previous work, in forecast cosmological analyses with the photometric galaxy sample of the Euclid survey. We aim to assess their impact and to quantify the bias on the measurement of cosmological parameters that would be caused if this effect were neglected. We performed this task by producing mock power spectra for photometric galaxy clustering and weak lensing, as is expected to be obtained from the Euclid survey. We then used a Markov chain Monte Carlo approach to obtain the posterior distributions of cosmological parameters from these simulated observations. When the linear RSD is neglected, significant biases are caused when galaxy correlations are used alone and when they are combined with cosmic shear in the so-called 3$\times$2pt approach. These biases can be equivalent to as much as $5\,σ$ when an underlying $Λ$CDM cosmology is assumed. When the cosmological model is extended to include the equation-of-state parameters of dark energy, the extension parameters can be shifted by more than $1\,σ$.

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Production of Alternate Realizations of DESI Fiber Assignment for Unbiased Clustering Measurement in Data and Simulations

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.

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Euclid preparation. Improving cosmological constraints using a new multi-tracer method with the spectroscopic and photometric samples

Future data provided by the Euclid mission will allow us to better understand the cosmic history of the Universe. A metric of its performance is the figure-of-merit (FoM) of dark energy, usually estimated with Fisher forecasts. The expected FoM has previously been estimated taking into account the two main probes of Euclid, namely the three-dimensional clustering of the spectroscopic galaxy sample, and the so-called 3x2pt signal from the photometric sample (i.e., the weak lensing signal, the galaxy clustering, and their cross-correlation). So far, these two probes have been treated as independent. In this paper, we introduce a new observable given by the ratio of the (angular) two-point correlation function of galaxies from the two surveys. For identical (normalised) selection functions, this observable is unaffected by sampling noise, and its variance is solely controlled by Poisson noise. We present forecasts for Euclid where this multi-tracer method is applied and is particularly relevant because the two surveys will cover the same area of the sky. This method allows for the exploitation of the combination of the spectroscopic and photometric samples. When the correlation between this new observable and the other probes is not taken into account, a significant gain is obtained in the FoM, as well as in the constraints on other cosmological parameters. The benefit is more pronounced for a commonly investigated modified gravity model, namely the $γ$ parametrisation of the growth factor. However, the correlation between the different probes is found to be significant and hence the actual gain is uncertain. We present various strategies for circumventing this issue and still extract useful information from the new observable.

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Full Modeling and Parameter Compression Methods in configuration space for DESI 2024 and beyond

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 $1σ$ 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.

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Optimal Reconstruction of Baryon Acoustic Oscillations for DESI 2024

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.

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Impact of Systematic Redshift Errors on the Cross-correlation of the Lyman-$α$ Forest with Quasars at Small Scales Using DESI Early Data

The Dark Energy Spectroscopic Instrument (DESI) will measure millions of quasar spectra by the end of its 5 year survey. Quasar redshift errors impact the shape of the Lyman-$α$ forest correlation functions, which can affect cosmological analyses and therefore cosmological interpretations. Using data from the DESI Early Data Release and the first two months of the main survey, we measure the systematic redshift error from an offset in the cross-correlation of the Lyman-$α$ forest with quasars. We find evidence for a redshift dependent bias causing redshifts to be underestimated with increasing redshift, stemming from improper modeling of the Lyman-$α$ optical depth in the templates used for redshift estimation. New templates were derived for the DESI Year 1 quasar sample at $z > 1.6$ and we found the redshift dependent bias, $Δr_\parallel$, increased from $-1.94 \pm 0.15$ $h^{-1}$ Mpc to $-0.08 \pm 0.04$ $h^{-1}$ Mpc ($-205 \pm 15~\text{km s}^{-1}$ to $-9.0 \pm 4.0~\text{km s}^{-1}$). These new templates will be used to provide redshifts for the DESI Year 1 quasar sample.

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HOD-Dependent Systematics in Emission Line Galaxies for the DESI 2024 BAO analysis

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 $α_\text{iso}$ within 0.1\% and the Alcock Paczynski parameter $α_\text{AP}$ 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.

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