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

We study the [OII] profiles of emission line galaxies (ELGs) from the Early Data Release of the Dark Energy Spectroscopic Instrument (DESI). To this end, we decompose and classify the shape of [OII] profiles with the first two eigenspectra derived from Principal Component Analysis. Our results show that DESI ELGs have diverse line profiles which can be categorized into three main types: (1) narrow lines with a median width of ~50 km/s, (2) broad lines with a median width of ~80 km/s, and (3) two-redshift systems with a median velocity separation of ~150 km/s, i.e., double-peak galaxies. To investigate the connections between the line profiles and galaxy properties, we utilize the information from the COSMOS dataset and compare the properties of ELGs, including star-formation rate (SFR) and galaxy morphology, with the average properties of reference star-forming galaxies with similar stellar mass, sizes, and redshifts. Our findings show that on average, DESI ELGs have higher SFR and more asymmetrical/disturbed morphology than the reference galaxies. Moreover, we uncover a relationship between the line profiles, the excess SFR and the excess asymmetry parameter, showing that DESI ELGs with broader [OII] line profiles have more disturbed morphology and higher SFR than the reference star-forming galaxies. Finally, we discuss possible physical mechanisms giving rise to the observed relationship and the implications of our findings on the galaxy clustering measurements, including the halo occupation distribution modeling of DESI ELGs and the observed excess velocity dispersion of the satellite ELGs., Comment: 24 pages, 13 figures, submitted to ApJ

Aims. We present an extensive catalog of the physical properties of more than a million galaxies within the Dark Energy Spectroscopic Instrument (DESI), one of the largest spectroscopic surveys to date. Spanning over a full variety of target types, including emission line galaxies and luminous red galaxies as well as quasars, our survey encompasses an unprecedented range of spectroscopic redshifts, stretching from 0 to 6. Methods. The physical properties, such as stellar masses and star formation rates, are derived via the CIGALE spectral energy distribution (SED) fitting code accounting for the contribution coming from active galactic nuclei (AGN). Based on the modeling of the optical-mid-infrared (grz complemented by WISE photometry) SEDs, we study galaxy properties with respect to their location on the main sequence. Results. We revise the dependence of stellar mass estimates on model choices and availability of the WISE photometry. The WISE information is mandatory to minimize the misclassification of star-forming galaxies as AGN. The lack of WISE bands in SED fits leads to elevated AGN fractions for 68% of star-forming galaxies identified using emission line diagnostic diagram but does not significantly affect their stellar mass nor star formation estimates., Comment: resubmitted after addressing minor referee comments

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

Galaxy scaling relations provide insights into the processes that drive galaxy evolution. The extension of these scaling relations into the dwarf galaxy regime is of particular interest. This is because dwarf galaxies represent a crucial stage in galaxy evolution, and understanding them could also shed light on their role in reionising the early Universe. There is currently no consensus on the processes that dominate the evolution of dwarfs. In this work we constrain the atomic gas sequence (stellar mass vs. atomic gas fraction) and mass-metallicity relation (stellar mass vs. gas phase metallicity) from dwarf ($10^{6.5}$ $\textrm{M}_{\odot}$) to massive ($10^{11.5}$ $\textrm{M}_{\odot}$) galaxies in the local Universe. The combined optical and 21-cm spectroscopic observations of the DESI and ALFALFA surveys allow us to simultaneously constrain both scaling relations. We find a slope change of the atomic gas sequence at a stellar mass of $\sim 10^{9} ~\textrm{M}_{\odot}$. We also find that the shape and scatter of the atomic gas sequence and mass-metallicity relation are strongly linked for both dwarfs and more massive galaxies. Consequently, the low mass slope change of the atomic gas sequence is imprinted onto the mass-metallicity relation of dwarf galaxies. The mass scale of the measured slope change is consistent with a predicted escape velocity threshold below which low mass galaxies experience significant supernova-driven gas loss, as well as with a reduction in cold gas accretion onto more massive galaxies., Comment: 16 pages, 10 figures, submitted to MNRAS

We present a measurement of the mean absorption of cool gas traced by Mg II (${\lambda\lambda 2796, 2803}$) around emission line galaxies (ELGs), spanning spatial scales from 20 kpc to 10 Mpc. The measurement is based on cross-matching the positions of about 2.5 million ELGs at $z = 0.75-1.65$ and the metal absorption in the spectra of 1.4 million background quasars with data provided by the Year 1 sample of the Dark Energy Spectroscopic Instrument (DESI). The ELGs are divided into two redshift intervals: $0.75 < z < 1.0$ and $1.0 < z < 1.65$. We find that the composite spectra constructed by stacking the ELG-QSO pairs show evolution with redshift, with $z>1$ having a systematically higher signal of Mg II absorption. Within 1 Mpc, the covering fraction of the cool gas at $z > 1$ is higher than that of $z < 1$. The enhancement becomes less apparent especially if the projected distance $r_{p}>$1 Mpc. Also, ELGs with higher stellar mass and star formation rate (SFR) yield higher clustering of Mg II absorbers at $z<1$. For $z>1$, the covering fractions with different SFRs show little difference. The higher Mg II absorption at higher redshift also supports the observations of higher star formation at cosmic noon. Besides, the profile of Mg II absorption reveals a change of slope on scales of about 1 Mpc, consistent with the expected transition from a dark matter halo-dominated environment to a regime where clustering is dominated by halo-halo correlations. We estimate the cool gas density profile and derive the metal abundance at different redshifts. The growth of metal abundance suggests an increased presence of cool gas in the intergalactic medium (IGM) towards higher redshifts.

We evaluate the performance of the catalog-level blind analysis technique (\textit{blinding}) presented in Brieden et al. (2020) in the context of a power spectrum and bispectrum analysis. This blinding scheme, which is tailored for galaxy redshift surveys similar to the Dark Energy Spectroscopic Instrument (DESI), has two components: the so-called "AP blinding" (Alcock-Paczy\'nski, concerning the dilation parameters $\alpha_\parallel,\alpha_\bot$) and "RSD blinding" (redshift space distortions, affecting the growth rate parameter $f$). Through extensive testing, including checks for the RSD part in cubic boxes, the impact of AP blinding on mocks with realistic survey sky coverage, and the implementation of a full AP+RSD blinding pipeline, our analysis demonstrates the effectiveness of the technique in preserving the integrity of cosmological parameter estimation when the analysis includes the bispectrum statistic. We emphasize the critical role of sophisticated -- and difficult to accidentally unblind -- blinding methods in precision cosmology.

Highly-multiplexed, robotic, fiber-fed spectroscopic surveys are observing tens of millions of stars and galaxies. For many systems, accurate positioning relies on imaging the fibers in the focal plane and feeding that information back to the robotic positioners to correct their positions. Inhomogeneities and turbulence in the air between the focal plane and the imaging camera can affect the measured positions of fibers, limiting the accuracy with which fibers can be placed on targets. For the Dark Energy Spectroscopic Instrument, we dramatically reduced the effect of turbulence on measurements of positioner locations in the focal plane by taking advantage of stationary positioners and the correlation function of the turbulence. We were able to reduce positioning errors from 7.3 microns to 3.5 microns, speeding the survey by 1.6% under typical conditions., Comment: 11 pages, 5 figures

We present the stellar value-added catalogue based on the Dark Energy Spectroscopic Instrument (DESI) Early Data Release. The catalogue contains radial velocity and stellar parameter measurements for $\simeq$ 400,000 unique stars observed during commissioning and survey validation by DESI. These observations were made under conditions similar to the Milky Way Survey (MWS) currently carried out by DESI but also include multiple specially targeted fields, such as those containing well-studied dwarf galaxies and stellar streams. The majority of observed stars have $16

In this work we use Lagrangian perturbation theory to analyze the harmonic space galaxy clustering signal of Bright Galaxy Survey (BGS) and Luminous Red Galaxies (LRGs) targeted by the Dark Energy Spectroscopic Instrument (DESI), combined with the galaxy--galaxy lensing signal measured around these galaxies using Dark Energy Survey Year 3 source galaxies. The BGS and LRG galaxies are extremely well characterized by DESI spectroscopy and, as a result, lens galaxy redshift uncertainty and photometric systematics contribute negligibly to the error budget of our ``$2\times2$-point'' analysis. On the modeling side, this work represents the first application of the \texttt{spinosaurus} code, implementing an effective field theory model for galaxy intrinsic alignments, and we additionally introduce a new scheme (\texttt{MAIAR}) for marginalizing over the large uncertainties in the redshift evolution of the intrinsic alignment signal. Furthermore, this is the first application of a hybrid effective field theory (HEFT) model for galaxy bias based on the $\texttt{Aemulus}\, \nu$ simulations. Our main result is a measurement of the amplitude of the lensing signal, $S_8=\sigma_8 \left(\Omega_m/0.3\right)^{0.5} = 0.850^{+0.042}_{-0.050}$, consistent with values of this parameter derived from the primary CMB. This constraint is artificially improved by a factor of $51\%$ if we assume a more standard, but restrictive parameterization for the redshift evolution and sample dependence of the intrinsic alignment signal, and $63\%$ if we additionally assume the nonlinear alignment model. We show that when fixing the cosmological model to the best-fit values from Planck PR4 there is $> 5 \sigma$ evidence for a deviation of the evolution of the intrinsic alignment signal from the functional form that is usually assumed in cosmic shear and galaxy--galaxy lensing studies., Comment: 52 pages, 24 figures, to be submitted to PRD

With the number of supernovae observed expected to drastically increase thanks to large-scale surveys like the Dark Energy Spectroscopic Instrument (DESI), it is necessary that the tools we use to classify these objects keep up with this increase. We previously created Supernova Tagging and Classification (STag) to address this problem by employing machine learning techniques alongside logistic regression in order to assign 'tags' to spectra based on spectral features. STag II is a continuation of this work, which now makes use of model supernova spectra combined with real DESI spectra in order to train STag to better deal with realistic data. We also make use of the rlap score as a trustworthiness cut, making for a more robust and accurate supernova classifier than before., Comment: 27 pages, 7 figures. The STag code is available at https://github.com/wdavison909/STag

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

We measure the clustering of Lyman Alpha Emitting galaxies (LAEs) selected from the One-hundred-square-degree DECam Imaging in Narrowbands (ODIN) survey, with spectroscopic follow-up from Dark Energy Spectroscopic Instrument (DESI). We use DESI spectroscopy to optimize our selection and to constrain the interloper fraction and redshift distribution of our narrow-band selected sources. We select samples of 4000 LAEs at z=2.45 and 3.1 in 9 sq.deg. centered on the COSMOS field with median LyA fluxes of 10^{-16}erg/s/cm2. Covariances and cosmological inferences are obtained from a series of mock catalogs built upon high-resolution N-body simulations that match the footprint, number density, redshift distribution and observed clustering of the sample. We find that both samples have a correlation length of r_0=(3.0\pm 0.2)Mpc/h. Within our fiducial cosmology these correspond to 3D number densities of 10^{-3} h^3/Mpc^3 and, from our mock catalogs, biases of 1.7 and 2.0 at z=2.45 and 3.1, respectively. We discuss the implications of these measurements for the use of LAEs as large-scale structure tracers for high-redshift cosmology., Comment: 26 pages, 13 figures; minor revisions to match version accepted by JCAP

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.

Gravitationally lensed Type Ia supernovae (glSNe Ia) are unique astronomical tools for studying cosmological parameters, distributions of dark matter, the astrophysics of the supernovae and the intervening lensing galaxies themselves. Only a few highly magnified glSNe Ia have been discovered by ground-based telescopes, such as the Zwicky Transient Facility (ZTF), but simulations predict the existence of a fainter, undetected population. We present a systematic search in the ZTF archive of alerts from 1 June 2019 to 1 September 2022. Using the AMPEL platform, we developed a pipeline that distinguishes candidate glSNe Ia from other variable sources. Initial cuts were applied to the ZTF alert photometry before forced photometry was obtained for the remaining candidates. Additional cuts were applied to refine the candidates based on their light curve colours, lens galaxy colours, and the resulting parameters from fits to the SALT2 SN Ia template. Candidates were also cross-matched with the DESI spectroscopic catalogue. Seven transients passed all the cuts and had an associated galaxy DESI redshift, which we present as glSN Ia candidates. While superluminous supernovae (SLSNe) cannot be fully rejected, two events, ZTF19abpjicm and ZTF22aahmovu, are significantly different from typical SLSNe and their light curves can be modelled as two-image glSN Ia systems. From this two-image modelling, we estimate time delays of 22 $\pm$ 3 and 34 $\pm$ 1 days for the two events, respectively, which suggests that we have uncovered a population with longer time delays. The pipeline is efficient and sensitive enough to parse full alert streams. It is currently being applied to the live ZTF alert stream to identify and follow-up future candidates while active. This pipeline could be the foundation for glSNe Ia searches in future surveys, like the Vera C. Rubin Observatory's Legacy Survey of Space and Time., Comment: 21 pages, 15 figures

The large scale structure catalogs within DESI Data Release 1 (DR1) use nearly 6 million galaxies and quasars as tracers of the large-scale structure of the universe to measure the expansion history with baryon acoustic oscillations and the growth of structure with redshift-space distortions. In order to take advantage of DESI's unprecedented statistical power, we must ensure that the galaxy clustering measurements are unaffected by non-cosmological density fluctuations. One source of spurious fluctuations comes from variation in galaxy density with spectroscopic observing conditions, lowering the redshift efficiency (and thus galaxy density) in certain areas of the sky. We measure the uniformity of the redshift success rate for DESI luminous red galaxies (LRG), bright galaxies (BGS) and quasars (QSO), complementing the detailed discussion of emission line galaxy (ELG) systematics in a companion paper (Yu et al., 2024). We find small but significant fluctuations of up to 3% in redshift success rate with the effective spectroscopic signal-to-noise, and create and describe weights that remove these fluctuations. We also describe the process to identify and remove data from certain poorly performing fibers from DESI DR1, and measure the stability of the redshift success rate with time. Finally, we find small but significant correlations of redshift success rate with position on the focal plane, survey speed, and number of exposures required, and show the impact of weights correcting these trends on the power spectrum multipoles and on cosmological parameters from BAO and RSD fits. These corrections change the best-fit parameters by $<15\%$ of their statistical errors, and thus contribute negligibly to the overall DESI error budget., Comment: 53 pages, 41 figures. Supporting paper for DESI DR1 cosmological measurements

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

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 $\sigma_8$ and other cosmological parameters. We detect \bispeconed\ with $4.8\sigma$ 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., Comment: 13 pages excluding references, 8 figures

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 $\Lambda$ despite dark energy dynamics). All three classes fit the data at least as well as $\Lambda$CDM, and indeed can improve on it by $\Delta\chi^2\approx -5$ 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., Comment: 20 pages, 8 figures. Metadata updated, comments welcome

Broad absorption line quasars (BALs) exhibit blueshifted absorption relative to a number of their prominent broad emission features. These absorption features can contribute to quasar redshift errors and add absorption to the Lyman-alpha (LyA) forest that is unrelated to large-scale structure. We present a detailed analysis of the impact of BALs on the Baryon Acoustic Oscillation (BAO) results with the LyA forest from the first year of data from the Dark Energy Spectroscopic Instrument (DESI). The baseline strategy for the first year analysis is to mask all pixels associated with all BAL absorption features that fall within the wavelength region used to measure the forest. We explore a range of alternate masking strategies and demonstrate that these changes have minimal impact on the BAO measurements with both DESI data and synthetic data. This includes when we mask the BAL features associated with emission lines outside of the forest region to minimize their contribution to redshift errors. We identify differences in the properties of BALs in the synthetic datasets relative to the observational data, as well as use the synthetic observations to characterize the completeness of the BAL identification algorithm, and demonstrate that incompleteness and differences in the BALs between real and synthetic data also do not impact the BAO results for the LyA forest., Comment: 32 pages, 8 figures, accepted by JCAP

We explore the influence of radio-mode feedback on the properties of the cool circumgalactic medium (CGM). To this end, we assemble a statistical sample of approximately 30,000 radio galaxies with background quasars by combining optical spectroscopic measurements of luminous red galaxies (LRGs) and quasars from the year 1 dataset of Dark Energy Spectroscopic Instrument (DESI) and radio sources from the LOw-Frequency ARray Two-metre Sky Survey (LoTSS) DR2 catalog and the Very Large Array Sky Survey (VLASS) quick look catalog. Galaxies with similar optical properties but with no radio counterparts in LoTSS and VLASS are selected as the control group. We measure the cool CGM properties of radio galaxies and their control samples traced by MgII absorption lines, including covering fraction, rest equivalent width, and gas kinematics. Our results show no significant difference in the properties of gas around radio galaxies and their control sample, indicating that the operating radio-mode feedback of massive galaxies does not produce detectable effects on the properties of the cool CGM. Finally, we show that the CGM of radio galaxies contain a non-negligible amount of cool gas with approximately 10^10 solar masses. This abundance can place a stringent constraint on the radio-mode feedback models., Comment: 20 pages, 12 figures

We present the Lyman-$\alpha$ Continuum Analysis Network (LyCAN), a Convolutional Neural Network that predicts the unabsorbed quasar continuum within the rest-frame wavelength range of $1040-1600$ Angstroms based on the red side of the Lyman-$\alpha$ emission line ($1216-1600$ Angstroms). We developed synthetic spectra based on a Gaussian Mixture Model representation of Nonnegative Matrix Factorization (NMF) coefficients. These coefficients were derived from high-resolution, low-redshift ($z<0.2$) Hubble Space Telescope/Cosmic Origins Spectrograph quasar spectra. We supplemented this COS-based synthetic sample with an equal number of DESI Year 5 mock spectra. LyCAN performs extremely well on testing sets, achieving a median error in the forest region of 1.5% on the DESI mock sample, 2.0% on the COS-based synthetic sample, and 4.1% on the original COS spectra. LyCAN outperforms Principal Component Analysis (PCA)- and NMF-based prediction methods using the same training set by 40% or more. We predict the intrinsic continua of 83,635 DESI Year 1 spectra in the redshift range of $2.1 \leq z \leq 4.2$ and perform an absolute measurement of the evolution of the effective optical depth. This is the largest sample employed to measure the optical depth evolution to date. We fit a power-law of the form $\tau(z) = \tau_0 (1+z)^\gamma$ to our measurements and find $\tau_0 = (2.46 \pm 0.14)\times10^{-3}$ and $\gamma = 3.62 \pm 0.04$. Our results show particular agreement with high-resolution, ground-based observations around $z = 2$, indicating that LyCAN is able to predict the quasar continuum in the forest region with only spectral information outside the forest., Comment: 23 pages, 15 figures, 3 tables; accepted to ApJ

We implement Crossing Statistics to reconstruct in a model-agnostic manner the expansion history of the universe and properties of dark energy, using DESI Data Release 1 (DR1) BAO data in combination with one of three different supernova compilations (PantheonPlus, Union3, and DES-SN5YR) and Planck CMB observations. Our results hint towards an evolving and emergent dark energy behaviour, with negligible presence of dark energy at $z\gtrsim 1$, at varying significance depending on data sets combined. In all these reconstructions, the cosmological constant lies outside the 95\% confidence intervals for some redshift ranges. This dark energy behaviour, reconstructed using Crossing Statistics, is in agreement with results from the conventional $w_0$--$w_a$ dark energy equation of state parametrization reported in the DESI Key cosmology paper. Our results add an extensive class of model-agnostic reconstructions with acceptable fits to the data, including models where cosmic acceleration slows down at low redshifts. We also report constraints on \Hord\ from our model-agnostic analysis, independent of the pre-recombination physics., Comment: 24 pages, 10 figures

The Dark Energy Spectroscopic Instrument (DESI) survey will measure spectroscopic redshifts for millions of galaxies across roughly $14,000 \, \mathrm{deg}^2$ of the sky. Cross-correlating targets in the DESI survey with complementary imaging surveys allows us to measure and analyze shear distortions caused by gravitational lensing in unprecedented detail. In this work, we analyze a series of mock catalogs with ray-traced gravitational lensing and increasing sophistication to estimate systematic effects on galaxy-galaxy lensing estimators such as the tangential shear $\gamma_{\mathrm{t}}$ and the excess surface density $\Delta\Sigma$. We employ mock catalogs tailored to the specific imaging surveys overlapping with the DESI survey: the Dark Energy Survey (DES), the Hyper Suprime-Cam (HSC) survey, and the Kilo-Degree Survey (KiDS). Among others, we find that fiber incompleteness can have significant effects on galaxy-galaxy lensing estimators but can be corrected effectively by up-weighting DESI targets with fibers by the inverse of the fiber assignment probability. Similarly, we show that intrinsic alignment and lens magnification are expected to be statistically significant given the precision forecasted for the DESI year-1 data set. Our study informs several analysis choices for upcoming cross-correlation studies of DESI with DES, HSC, and KiDS., Comment: 18 pages, 13 figures, version accepted for publication

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)

DESI aims to provide one of the tightest constraints on cosmological parameters by analysing the clustering of more than thirty million galaxies. However, obtaining such constraints requires special care in validating the methodology and efforts to reduce the computational time required through data compression and emulation techniques. In this work, we perform a rigorous validation of the PyBird power spectrum modelling code with both a traditional emulated Full-Modelling approach and the model-independent ShapeFit compression approach. By using cubic box simulations that accurately reproduce the clustering and precision of the DESI survey, we find that the cosmological constraints from ShapeFit and Full-Modelling are consistent with each other at the $\sim0.5\sigma$ level for the $\Lambda$CDM model. Both ShapeFit and Full-Modelling are also consistent with the true $\Lambda$CDM simulation cosmology down to a scale of $k_{\mathrm{max}} = 0.20 h\mathrm{Mpc}^{-1}$ even after including the hexadecapole. For extended models such as the wCDM and the oCDM models, we find that including the hexadecapole can significantly improve the constraints and reduce the modelling errors with the same $k_{\mathrm{max}}$. While their discrepancies between the constraints from ShapeFit and Full-Modelling are more significant than $\Lambda$CDM, they remain consistent within $0.7\sigma$. Lastly, we also show that the constraints on cosmological parameters with the correlation function evaluated from PyBird down to $s_{\mathrm{min}} = 30 h^{-1} \mathrm{Mpc}$ are unbiased and consistent with the constraints from the power spectrum., Comment: Supporting publication of DESI 2024 V: Analysis of the full shape of two-point clustering statistics from galaxies and quasars (In prep). 51 pages, 21 figures, and 12 tables. 2nd revised version for JCAP

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) cosmology survey includes a Bright Galaxy Survey (BGS) which will yield spectra for over ten million bright galaxies (r<20.2 AB mag). The resulting sample will be valuable for both cosmological and astrophysical studies. However, the star/galaxy separation criterion implemented in the nominal BGS target selection algorithm excludes quasar host galaxies in addition to bona fide stars. While this excluded population is comparatively rare (~3-4 per square degrees), it may hold interesting clues regarding galaxy and quasar physics. Therefore, we present a target selection strategy that was implemented to recover these missing active galactic nuclei (AGN) from the BGS sample. The design of the selection criteria was both motivated and confirmed using spectroscopy. The resulting BGS-AGN sample is uniformly distributed over the entire DESI footprint. According to DESI survey validation data, the sample comprises 93% quasi-stellar objects (QSOs), 3% narrow-line AGN or blazars with a galaxy contamination rate of 2% and a stellar contamination rate of 2%. Peaking around redshift z=0.5, the BGS-AGN sample is intermediary between quasars from the rest of the BGS and those from the DESI QSO sample in terms of redshifts and AGN luminosities. The stacked spectrum is nearly identical to that of the DESI QSO targets, confirming that the sample is dominated by quasars. We highlight interesting small populations reaching z>2 which are either faint quasars with nearby projected companions or very bright quasars with strong absorption features including the Lyman-apha forest, metal absorbers and/or broad absorption lines., Comment: 41 pages, 31 figures, submitted to the AAS journals. Comments are welcome

Ongoing and upcoming galaxy redshift surveys, such as the Dark Energy Spectroscopic Instrument (DESI) survey, will observe vast regions of sky and a wide range of redshifts. In order to model the observations and address various systematic uncertainties, N-body simulations are routinely adopted, however, the number of large simulations with sufficiently high mass resolution is usually limited by available computing time. Therefore, achieving a simulation volume with the effective statistical errors significantly smaller than those of the observations becomes prohibitively expensive. In this study, we apply the Convergence Acceleration by Regression and Pooling (CARPool) method to mitigate the sample variance of the DESI-like galaxy clustering in the AbacusSummit simulations, with the assistance of the quasi-N-body simulations FastPM. Based on the halo occupation distribution (HOD) models, we construct different FastPM galaxy catalogs, including the luminous red galaxies (LRGs), emission line galaxies (ELGs), and quasars, with their number densities and two-point clustering statistics well matched to those of AbacusSummit. We also employ the same initial conditions between AbacusSummit and FastPM to achieve high cross-correlation, as it is useful in effectively suppressing the variance. Our method of reducing noise in clustering is equivalent to performing a simulation with volume larger by a factor of 5 and 4 for LRGs and ELGs, respectively. We also mitigate the standard deviation of the LRG bispectrum with the triangular configurations $k_2=2k_1=0.2$ h/Mpc by a factor of 1.6. With smaller sample variance on galaxy clustering, we are able to constrain the baryon acoustic oscillations (BAO) scale parameters to higher precision. The CARPool method will be beneficial to better constrain the theoretical systematics of BAO, redshift space distortions (RSD) and primordial non-Gaussianity (NG)., Comment: 37 pages, 15 figures, 3 tables, matched to the accepted version of JCAP; comments welcome

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 can be measured with sub-percent precision above redshift two with the Lyman-alpha forest auto-correlation and its cross-correlation with quasar positions. This is one of the key goals of the Dark Energy Spectroscopic Instrument (DESI) which started its main survey in May 2021. We present in this paper a study of the contaminants to the lyman-alpha forest which are mainly caused by correlated signals introduced by the spectroscopic data processing pipeline as well as astrophysical contaminants due to foreground absorption in the intergalactic medium. Notably, an excess signal caused by the sky background subtraction noise is present in the lyman-alpha auto-correlation in the first line-of-sight separation bin. We use synthetic data to isolate this contribution, we also characterize the effect of spectro-photometric calibration noise, and propose a simple model to account for both effects in the analysis of the lyman-alpha forest. We then measure the auto-correlation of the quasar flux transmission fraction of low redshift quasars, where there is no lyman-alpha forest absorption but only its contaminants. We demonstrate that we can interpret the data with a two-component model: data processing noise and triply ionized Silicon and Carbon auto-correlations. This result can be used to improve the modeling of the lyman-alpha auto-correlation function measured with DESI., Comment: 32 pages, 12 figures

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

The first year of data from the Dark Energy Spectroscopic Instrument (DESI) contains the largest set of Lyman-$\alpha$ (Ly$\alpha$) 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$\alpha$ 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$\alpha$ forest. The synthetic data sets span a redshift range $1.8

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