While the Lyman-alpha(Ly alpha) forest traces the large-scale matter distribution over a wide range of redshift, its three-dimensional clustering at z < 2 has not yet been measured. We investigate the prospects for measuring low-redshift Ly alpha correlations with the UV slitless spectroscopic instrument of the Chinese Space Station Telescope (CSST). We construct mock CSST quasar spectra that reproduce the expected survey depth, spectral resolution and noise properties, and derive Ly alpha auto-correlation functions and cross-correlations with quasars (QSO) and emission-line galaxies (ELG) in the range 1.1 < z <2.0. We then interpret these three-dimensional correlation functions with a standard anisotropic redshift-space clustering model and obtain forecast constraints on the Ly alpha and tracer parameters. At an effective redshift z(eff) = 1.59 (1.58 for ELGs), the Ly alpha bias parameters will be measured with a 10-30% precision, depending on priors on other tracer's biases. We also forecast a marginal 2.5 sigma (3.7 sigma) detection of the BAO feature, corresponding to a similar to 10% (7%) constraint on the isotropic BAO scale, from the combination of Ly alpha auto-and Ly alpha-QSO (ELG) cross-correlations. These results show that CSST can provide the first three-dimensional characterization of the low-redshift Ly alpha forest and a complementary Ly alpha-based BAO measurement at z < 2, helping to link galaxy clustering surveys with high-redshift Ly alpha forest studies.

The Data Release 1 (DR1) of the Dark Energy Spectroscopic Instrument (DESI) is the largest sample to date for small-scale Ly alpha forest cosmology, accessed through its one-dimensional power spectrum (P1D). The Ly alpha forest P-1D is extracted from quasar spectra that are highly inhomogeneous (both in wavelength and between quasars) in noise properties due to intrinsic properties of the quasar, atmospheric and astrophysical contamination, and also sensitive to low-level details of the spectral extraction pipeline. We employ two estimators in DR1 analysis to measure P-1D: the optimal estimator and the fast Fourier transform (FFT) estimator. To ensure robustness of our DR1 measurements, we validate these two power spectrum and covariance matrix estimation methodologies against the challenging aspects of the data. First, using a set of 20 synthetic 1D realizations of DR1, we derive the masking bias corrections needed for the FFT estimator and the continuum fitting bias needed for both estimators. We demonstrate that both estimators, including their covariances, are unbiased with these corrections using the Kolmogorov-Smirnov test. Second, we substantially extend our previous suite of CCD image simulations to include 675,000 quasars, allowing us to accurately quantify the pipeline's performance. This set of simulations reveals biases at the highest k values, corresponding to a resolution error of a few percent. We base the resolution systematics error budget of DR1 P-1D on these values, but do not derive corrections from them since the simulation fidelity is insufficient for precise corrections.

In this short course, which complements the lecture on Dark Matter alternatives, I provide concrete examples of how Dark Matter (DM) models can be tested, whether for generic DM properties, or specific scenarios. First, I review searches for WIMPs, one of the most well-studied DM candidates. I also showcase some constraints on DM models that predict a modification of the cosmological matter power spectrum at high $k$. To this end, I focus primarily on bounds derived from the Lyman-$\alpha$ forest observations, which I will present in a brief overview beforehand.

We present a multi-redshift Baryon Acoustic Oscillations (BAO) analysis of the DESI Data Release 2 (DR2) Lyman-α (Lyα) forest, splitting the forest auto-correlation and its cross-correlation with quasars into three redshift bins. We obtain BAO measurements at effective redshifts z_ eff = 2.13, 2.40, and 2.81 with ∼2.0–2.5% precision per bin in the radial and transverse directions, corresponding to ∼1.1–1.2% precision for the isotropic BAO measurement. Using the same data products and modeling framework as the DESI DR2 Lyα BAO analysis, we validate the pipeline on 400 synthetic datasets and find unbiased BAO recovery with well-calibrated uncertainties. The measurements show an increase in the isotropic dilation parameter D_V/r_d from 30.26±0.39 to 32.22±0.47 and in the Alcock-Paczyński parameter D_M/D_H from 3.96±0.15 to to 5.63^+0.22_-0.24. The Hubble distance D_H/r_d decreases from 9.40±0.20 to 7.22±0.17, providing a direct measurement of the expansion history consistent with ΛCDM and the expected matter-dominated scaling, with H(z)∝(1+z)^n giving n=1.34±0.16. The redshift split also provides a self-consistent measurement of clustering evolution: the Lyα forest bias evolves as (1+z)^γ with γ_α=3.05±0.16, the RSD parameter has a redshift evolution described by γ_β=-0.97±0.26, and the quasar bias evolves with γ_Q=1.56±0.23, consistent with independent quasar clustering measurements. Combining these three-bin BAO measurements with DESI DR2 galaxy and quasar BAO measurements yields cosmological constraints consistent with the single-bin Lyα BAO analysis in flat ΛCDM and w_0w_aCDM and improves curvature constraints by ∼12% in ΛCDM+Ω_K.

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.

We present the Lyssa suite of high-resolution cosmological simulations of the Lyman- α forest designed for cosmological analyses. These 18 simulations have been run using the Nyx code with 4096 3 hydrodynamical cells in a 120 Mpc (∼ 81 Mpc/ h ) comoving box and individually provide sub-percent level convergence of the Lyman- α forest 1d flux power spectrum. We build a Gaussian process emulator for the Lyssa simulations in the lym1d likelihood framework to interpolate the power spectrum at arbitrary parameter values. We validate this emulator based on leave-one-out tests and based on the parameter constraints for simulations outside of the training set. We also perform comparisons with a previous emulator, showing a percent level accuracy and a good recovery of the expected cosmological parameters. Using this emulator we derive constraints on the linear matter power spectrum amplitude and slope parameters A Ly α and n Ly α . While the best-fit Planck ΛCDM model has A Ly α = 8.79 and n Ly α = -2.363, from DR14 eBOSS data we find that A Ly α < 7.6 (95% CI) and n Ly α = -2.369 ± 0.008. The low value of A Ly α , in tension with Planck, is driven by the correlation of this parameter with the mean transmission of the Lyman- α forest. This tension disappears when imposing a well-motivated external prior on this mean transmission, in which case we find A Ly α = 9.8 ± 1.1 in accordance with Planck.

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 presented in [1]. 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 < z < 3.8, and are analysed using the same framework and pipeline used for the DESI 2024 Ly alpha forest BAO measurement. To measure BAO, we use both the Ly alpha auto-correlation and its crosscorrelation 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 alpha forest correlation functions. Finally, we discuss the implications of our results and identify the needs for the next generation of Ly alpha forest synthetic data sets, with the top priority being to simulate the effect of BAO broadening due to non-linear evolution.

We present the measurements and cosmological implications of the galaxy two-point clustering using over 4.7 million unique galaxy and quasar redshifts in the range 0.1 < z < 2.1 divided into six redshift bins over a similar to 7, 500 square degree footprint, from the first year of observations with the Dark Energy Spectroscopic Instrument (DESI Data Release 1). By fitting the full power spectrum, we extend previous DESI DR1 baryon acoustic oscillation (BAO) measurements to include redshift-space distortions and signals from the matter-radiation equality scale. For the first time, this Full-Shape analysis is blinded at the catalogue-level to avoid confirmation bias and the systematic errors are accounted for at the two-point clustering level, which automatically propagates them into any cosmological parameter. When analysing the data in terms of compressed model-agnostic variables, we obtain a combined precision of 4.7% on the amplitude of the redshift space distortion (RSD) signal reaching a similar precision with just one year of DESI data than with twenty years of observation from the previous generation survey. We also analyse the data to directly constrain the cosmological parameters within the Lambda CDM model using perturbation theory and combine this information with the reconstructed DESI DR1 galaxy BAO. Using a Big Bang Nucleosynthesis Gaussian prior on the baryon density parameter, omega(b), and a weak Gaussian prior on the spectral index, n(s), we constrain the matter density is Omega(m) = 0.296 +/- 0.010 and the Hubble constant H-0 = (68.63 +/- 0.79)[km s(-1)Mpc(-1)]. Additionally, we measure the amplitude of clustering sigma(8) = 0.841 +/- 0.034. The DESI DR1 galaxy clustering results are in agreement with the Lambda CDM model based on general relativity with parameters consistent with those from Planck. The cosmological interpretation of these results in combination with DESI DR1 Ly-alpha forest data and external datasets are presented in the companion paper [1].

Synthetic data sets are used in cosmology to test analysis procedures, to verify that systematic errors are well understood and to demonstrate that measurements are unbiased. In this work we describe the methods used to generate synthetic datasets of Lyman-$\alpha$ quasar spectra aimed for studies with the Dark Energy Spectroscopic Instrument (DESI). In particular, we focus on demonstrating that our simulations reproduces important features of real samples, making them suitable to test the analysis methods to be used in DESI and to place limits on systematic effects on measurements of Baryon Acoustic Oscillations (BAO). We present a set of mocks that reproduce the statistical properties of the DESI early data set with good agreement. Additionally, we use full survey synthetic data to forecast the BAO scale constraining power with DESI.

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.]

We present the one-dimensional Lyman-alpha forest power spectrum measurement derived from the data release 1 (DR1) of the Dark Energy Spectroscopic Instrument (DESI). The measurement of the Lyman-alpha forest power spectrum along the line of sight from highredshift quasar spectra provides information on the shape of the linear matter power spectrum, neutrino masses, and the properties of dark matter. In this work, we use a Fast Fourier Transform (FFT)-based estimator, which is validated on synthetic data in a companion paper. Compared to the FFT measurement performed on the DESI early data release, we improve the noise characterization with a cross-exposure estimator and test the robustness of our measurement using various data splits. We also refine the estimation of the uncertainties and now present an estimator for the covariance matrix of the measurement. Furthermore, we compare our results to previous high-resolution and eBOSS measurements. In another companion paper, we present the same DR1 measurement using the Quadratic Maximum Likelihood Estimator (QMLE). These two measurements are consistent with each other and constitute the most precise one-dimensional power spectrum measurement to date, while being in good agreement with results from the DESI early data release.

We present the measurement of Baryon Acoustic Oscillations (BAO) from the Lyman- a (Lya) forest of high-redshift quasars with the first-year dataset of the Dark Energy Spectroscopic Instrument (DESI). Our analysis uses over 420 000 Lya 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 ( rd), we measure the expansion at zeff = 2.33 with 2% precision, H(zeff) = (239.2 +/- 4.8) (147.09Mpc/ rd) km/s/Mpc. Similarly, we present a 2.4% measurement of the transverse comoving distance to the same redshift, DM (zeff) = (5.84 +/- 0.14) ( rd/147.09Mpc) Gpc. Together with other DESI BAO measurements at lower redshifts, these results are used in a companion paper to constrain cosmological parameters.

The Hobby–Eberly Dark Energy Experiment (HETDEX) is an untargeted spectroscopic galaxy survey that uses Ly α- emitting galaxies (LAEs) as tracers of 1.9 < z < 3.5 large-scale structure. Most detections consist of a single emission line, whose identity is inferred via a Bayesian analysis of ancillary data. To determine the accuracy of these line identifications, HETDEX detections were observed with the Dark Energy Spectroscopic Instrument (DESI). In two DESI pointings, high-confidence spectroscopic redshifts are obtained for 1157 sources, including 982 LAEs. The DESI spectra are used to evaluate the accuracy of the HETDEX object classifications and tune the methodology to achieve the HETDEX science requirement of ≲2% contamination of the LAE sample by low-redshift emission-line galaxies, while still assigning 96% of the true Ly α emission sample with the correct spectroscopic redshift. We compare emission-line measurements between the two experiments assuming a simple Gaussian line fitting model. Fitted values for the central wavelength of the emission line, the measured line flux, and line widths are consistent between the surveys within uncertainties. Derived spectroscopic redshifts, from the two classification pipelines, when both agree as an LAE classification, are consistent to within 〈Δ z /(1 + z )〉 = 6.9 × 10 ^−5 with an rms scatter of 3.3 × 10 ^−4 . Data are available at https://data.desi.lbl.gov/desi/public/dr1/vac/dr1/hetdex .

The Lyman-alpha (Ly alpha) forest is a key tracer of large-scale structure at redshifts z > 2, traditionally studied using the spectra of luminous but relatively rare quasars. In this work, we explore the viability of using the fainter yet significantly more abundant Lyman Break Galaxies (LBGs) as alternative background sources for Ly alpha forest studies. We analyze 4,151 Ly alpha forest skewers extracted from LBG spectra obtained in the DESI pilot surveys conducted in the COSMOS and XMM-LSS fields. From this dataset, we present the first measurement of the Ly alpha forest auto-correlation function derived exclusively from LBG spectra, probing comoving separations up to 48 h(-1) Mpc at an effective redshift of z(eff) = 2.70. The measured LBG Ly alpha forest auto-correlation is consistent with that derived from DESI DR2 quasar Ly alpha forest spectra at a comparable redshift, validating the use of LBGs as reliable background sources for Ly alpha forest analyses. In addition, we measure the cross-correlation between the LBG Ly alpha forest and the positions of 13,362 galaxies, demonstrating that this observable serves as a sensitive diagnostic for assessing the precision and accuracy of galaxy redshift estimates, and for identifying and correcting systematic offsets. Finally, using both synthetic LBG spectra and Fisher matrix forecasts, we show that a future wide-area survey covering similar to 5,000 deg(2), targeting 1,000 LBGs per square degree at signal-to-noise levels comparable to our sample, could enable LBG-based Ly alpha forest baryon acoustic oscillation (BAO) measurements with expected uncertainties of sigma(alpha ISO) = 0.4% (isotropic) and sigma(alpha AP) = 1.3% (Alcock-Paczynski). This performance is further enhanced when combining the BAO analysis with a Ly alpha forest Full Shape (FS) approach, yielding a predicted uncertainty of sigma(FS)(alpha AP) = 0.6%. These results open a new avenue for precision cosmology at high redshift using the Ly alpha forest in dense LBG samples.

We present the samples of galaxies and quasars used for DESI 2024 cosmological analyses, drawn from the DESI Data Release 1 (DR1). We describe the construction of large-scale structure (LSS) catalogs from these samples, which include matched sets of synthetic reference `randoms' and weights that account for variations in the observed density of the samples due to experimental design and varying instrument performance. We detail how we correct for variations in observational completeness, the input `target' densities due to imaging systematics, and the ability to confidently measure redshifts from DESI spectra. We then summarize how remaining uncertainties in the corrections can be translated to systematic uncertainties for particular analyses. We describe the weights added to maximize the signal-to-noise of DESI DR1 2-point clustering measurements. We detail measurement pipelines applied to the LSS catalogs that obtain 2-point clustering measurements in configuration and Fourier space. The resulting 2-point measurements depend on window functions and normalization constraints particular to each sample, and we present the corrections required to match models to the data. We compare the configuration- and Fourier-space 2-point clustering of the data samples to that recovered from simulations of DESI DR1 and find they are, generally, in statistical agreement to within 2% in the inferred real-space over-density field. The LSS catalogs, 2-point measurements, and their covariance matrices will be released publicly with DESI DR1.

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 < z < 2.1. Divided by tracer type, we utilize 300,017 galaxies from the magnitude-limited Bright Galaxy Survey with 0.1 < z < 0.4, 2,138,600 Luminous Red Galaxies with 0.4 < z < 1.1, 2,432,022 Emission Line Galaxies with 0.8 < z < 1.6, and 856,652 quasars with 0.8 < z < 2.1, over a ∼ 7,500 square degree footprint. The analysis was blinded at the catalog-level to avoid confirmation bias. All fiducial choices of the BAO fitting and reconstruction methodology, as well as the size of the systematic errors, were determined on the basis of the tests with mock catalogs and the blinded data catalogs. We present several improvements to the BAO analysis pipeline, including enhancing the BAO fitting and reconstruction methods in a more physically-motivated direction, and also present results using combinations of tracers. We employ a unified BAO analysis method across all tracers. We present a re-analysis of SDSS BOSS and eBOSS results applying the improved DESI methodology and find scatter consistent with the level of the quoted SDSS theoretical systematic uncertainties. With the total effective survey volume of ∼ 18 Gpc 3 , the combined precision of the BAO measurements across the six different redshift bins is ∼0.52%, marking a 1.2-fold improvement over the previous state-of-the-art results using only first-year data. We detect the BAO in all of these six redshift bins. The highest significance of BAO detection is 9.1σ at the effective redshift of 0.93, with a constraint of 0.86% placed on the BAO scale. We find that our observed BAO scales are systematically larger than the prediction of the Planck 2018-ΛCDM at z < 0.8. We translate the results into transverse comoving distance and radial Hubble distance measurements, which are used to constrain cosmological models in our companion paper.

Cosmological information is usually extracted from the Lyman-alpha (Ly alpha) forest correlations using only either large-scale information interpreted through linear theory or using small-scale information interpreted by means of expensive hydrodynamical simulations. A complete cosmological interpretation of the three-dimensional (3D) correlations at all measurable scales is challenged by the need of more realistic models including the complex growth of non-linear small scales that can only be studied within large hydrodynamical simulations. Past works were often limited by the trade-off between the simulated cosmological volume and the resolution of the low-density intergalactic medium from which the Ly alpha signal originates. We conduct a suite of hydrodynamical simulations of the intergalactic medium, including one of the largest Ly alpha simulations ever performed in terms of volume (640 h(-1)Mpc), alongside simulations in smaller volumes with resolutions up to 25 h-1kpc, which will be further improved to show resolution convergence in future studies. We compare the 3D Ly alpha power spectra (P-3D,P-alpha) predicted by those simulations to different non-linear models. The inferred Ly alpha bias and redshift space distortion parameters, b(alpha) and beta(alpha) are in remarkable agreement with those measured in SDSS (Sloan Digital Sky Survey) and DESI (Dark Energy Spectroscopic Instrument) data. We find that, contrary to intuition, the convergence of large-scale modes of the P-3D,P-alpha, which determines beta(alpha), is primarily influenced by the resolution of the simulation box through mode coupling, rather than the box size itself. Finally, we study the Baryon Acoustic Oscillation (BAO) signal encoded in P-3D,P-alpha. For the first time with a hydrodynamical simulation, we clearly detect the BAO signal; however, we only marginally detect its damping, associated with the non-linear growth of the structures.

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.

We present a publicly-available code to generate sets of mock Lyman-alpha(Ly alpha) alpha (Ly alpha ) forest data that have realistic large-scale correlations including those due to the Baryonic Acoustic Oscillations (BAO). The primary purpose of these mocks is to test the analysis procedures of the Extended Baryon Oscillation Survey (eBOSS) and the Dark Energy Spectroscopy Instrument (DESI) surveys. The transmitted flux fraction, F ( lambda ), of background quasars due to Ly alpha alpha absorption in the intergalactic medium (IGM) is simulated using the Fluctuating Gunn-Petterson Approximation (FGPA) applied to Gaussian random fields produced through the use of fast Fourier transforms (FFT). The output includes the IGMLy alpha alpha transmitted flux fraction along quasar lines of sight and a catalog of high-column- density systems appropriately placed at high-density regions of the IGM. This output serves as input to additional code that superimposes the IGM tranmission on realistic quasar spectra, adds absorption by high-column-density systems and metals, and simulates instrumental transmission and noise. Redshift space distortions (RSD) of the flux correlations are implemented by including the large-scale velocity-gradient field in the FGPA resulting in a correlation function of F ( lambda ) that can be accurately predicted. One hundred realizations have been produced over the 14,000 deg2 2 DESI survey footprint with 100 quasars per deg2. 2 . The analysis of these realizations shows that the correlations of F ( lambda ) follows the prediction within the accuracy of eBOSS survey. The most time-consuming part of the mock production occurs before application of the FGPA, and the existing pre-FGPA forests can be used to easily produce new mock sets with modified redshift-dependent bias parameters or observational conditions.

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