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Todd Claybaugh

Publications and source records attributed to Todd Claybaugh.

At least 91 records · Page 5Linked to original sources

Forward modeling fluctuations in the DESI LRGs target sample using image simulations

We use the forward modeling pipeline, Obiwan, to study the imaging systematics of the Luminous Red Galaxies (LRGs) targeted by the Dark Energy Spectroscopic Instrument (DESI). We update the Obiwan pipeline, which had previously been developed to simulate the optical images used to target DESI data, to further simulate WISE images in the infrared. This addition makes it possible to simulate the DESI LRGs sample, which utilizes WISE data in the target selection. Deep DESI imaging data combined with a method to account for biases in their shapes is used to define a truth sample of potential LRG targets. We simulate a total of 15 million galaxies to obtain a simulated LRG sample (Obiwan LRGs) that predicts the variations in target density due to imaging properties. We find that the simulations predict the trends with depth observed in the data, including how they depend on the intrinsic brightness of the galaxies. We observe that faint LRGs are the main contributing power of the imaging systematics trend induced by depth. We also find significant trends in the data against Galactic extinction that are not predicted by Obiwan. These trends depend strongly on the particular map of Galactic extinction chosen to test against, implying Large-Scale Structure systematic contamination (e.g. Cosmic-Infrared Background) in the Galactic extinction maps is a likely root cause. We additionally observe that the DESI LRGs sample exhibits a complex dependency on a combination of seeing, depth, and intrinsic galaxy brightness, which is not replicated by Obiwan, suggesting discrepancies between the current simulation settings and the actual observations. The detailed findings we present should be used to guide any observational systematics mitigation treatment for the clustering of the DESI LRG sample.

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High redshift LBGs from deep broadband imaging for future spectroscopic surveys

Lyman break galaxies (LBGs) are promising probes for clustering measurements at high redshift, $z>2$, a region only covered so far by Lyman-$α$ forest measurements. In this paper, we investigate the feasibility of selecting LBGs by exploiting the existence of a strong deficit of flux shortward of the Lyman limit, due to various absorption processes along the line of sight. The target selection relies on deep imaging data from the HSC and CLAUDS surveys in the $g,r,z$ and $u$ bands, respectively, with median depths reaching 27 AB in all bands. The selections were validated by several dedicated spectroscopic observation campaigns with DESI. Visual inspection of spectra has enabled us to develop an automated spectroscopic typing and redshift estimation algorithm specific to LBGs. Based on these data and tools, we assess the efficiency and purity of target selections optimised for different purposes. Selections providing a wide redshift coverage retain $57\%$ of the observed targets after spectroscopic confirmation with DESI, and provide an efficiency for LBGs of $83\pm3\%$, for a purity of the selected LBG sample of $90\pm2\%$. This would deliver a confirmed LBG density of $\sim 620$ deg$^{-2}$ in the range $2.3<z<3.5$ for a $r$-band limiting magnitude $r<24.2$. Selections optimised for high redshift efficiency retain $73\%$ of the observed targets after spectroscopic confirmation, with $89\pm4\%$ efficiency for $97\pm2\%$ purity. This would provide a confirmed LBG density of $\sim 470$ deg$^{-2}$ in the range $2.8<z<3.5$ for a $r$-band limiting magnitude $r<24.5$. A preliminary study of the LBG sample 3d-clustering properties is also presented and used to estimate the LBG linear bias. A value of $b_{LBG} = 3.3 \pm 0.2 (stat.)$ is obtained for a mean redshift of 2.9 and a limiting magnitude in $r$ of 24.2, in agreement with results reported in the literature.

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Detection of the large-scale tidal field with galaxy multiplet alignment in the DESI Y1 spectroscopic survey

We explore correlations between the orientations of small galaxy groups, or "multiplets", and the large-scale gravitational tidal field. Using data from the Dark Energy Spectroscopic Instrument (DESI) Y1 survey, we detect the intrinsic alignment (IA) of multiplets to the galaxy-traced matter field out to separations of 100 Mpc/h. Unlike traditional IA measurements of individual galaxies, this estimator is not limited by imaging of galaxy shapes and allows for direct IA detection beyond redshift z = 1. Multiplet alignment is a form of higher-order clustering, for which the scale-dependence traces the underlying tidal field and amplitude is a result of small-scale (< 1 Mpc/h) dynamics. Within samples of bright galaxies (BGS), luminous red galaxies (LRG) and emission-line galaxies (ELG), we find similar scale-dependence regardless of intrinsic luminosity or colour. This is promising for measuring tidal alignment in galaxy samples that typically display no intrinsic alignment. DESI's LRG mock galaxy catalogues created from the AbacusSummit N-body simulations produce a similar alignment signal, though with a 33% lower amplitude at all scales. An analytic model using a non-linear power spectrum (NLA) only matches the signal down to 20 Mpc/h. Our detection demonstrates that galaxy clustering in the non-linear regime of structure formation preserves an interpretable memory of the large-scale tidal field. Multiplet alignment complements traditional two-point measurements by retaining directional information imprinted by tidal forces, and contains additional line-of-sight information compared to weak lensing. This is a more effective estimator than the alignment of individual galaxies in dense, blue, or faint galaxy samples.

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Changing-look Active Galactic Nuclei from the Dark Energy Spectroscopic Instrument. II. Statistical Properties from the First Data Release

We present the identification of changing-look active galactic nuclei (CL-AGNs) from the Dark Energy Spectroscopic Instrument First Data Release and Sloan Digital Sky Survey Data Release 16 at z \leq 0.9. To confirm the CL-AGNs, we utilize spectral flux calibration assessment via an [O\,{\sc iii}]-based calibration, pseudo-photometry examination, and visual inspection. This rigorous selection process allows us to compile a statistical catalog of 561 CL-AGNs, encompassing 527 $\rm Hβ$, 149$\rm Hα$, and 129 Mg II CL behaviors. In this sample, we find 1) a 283:278 ratio of turn-on to turn-off CL-AGNs. 2) the critical value for CL events is confirmed around Eddington ratio \sim 0.01. 3) a strong correlation between the change in the luminosity of the broad emission lines (BEL) and variation in the continuum luminosity, with Mg II and $\rm Hβ$ displaying similar responses during CL phases. 4) the Baldwin-Phillips-Terlevich diagram for CL-AGNs shows no statistically difference from the general AGN catalog. 5) five CL-AGNs are associated with asymmetrical mid-infrared flares, possibly linked to tidal disruption events. Given the large CL-AGNs and the stochastic sampling of spectra, we propose that some CL events are inherently due to typical AGN variability during low accretion rates, particularly for CL events of the singular BEL. Finally, we introduce a Peculiar CL phase, characterized by a gradual decline over decades in the light curve and the complete disappearance of entire BEL in faint spectra, indicative of a real transition in the accretion disk.

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Local primordial non-Gaussianity from the large-scale clustering of photometric DESI luminous red galaxies

We use angular clustering of luminous red galaxies from the Dark Energy Spectroscopic Instrument (DESI) imaging surveys to constrain the local primordial non-Gaussianity parameter $\fnl$. Our sample comprises over 12 million targets, covering 14,000 square degrees of the sky, with redshifts in the range $0.2< z < 1.35$. We identify Galactic extinction, survey depth, and astronomical seeing as the primary sources of systematic error, and employ linear regression and artificial neural networks to alleviate non-cosmological excess clustering on large scales. Our methods are tested against simulations with and without $\fnl$ and systematics, showing superior performance of the neural network treatment. The neural network with a set of nine imaging property maps passes our systematic null test criteria, and is chosen as the fiducial treatment. Assuming the universality relation, we find $\fnl = 34^{+24(+50)}_{-44(-73)}$ at 68\%(95\%) confidence. We apply a series of robustness tests (e.g., cuts on imaging, declination, or scales used) that show consistency in the obtained constraints. We study how the regression method biases the measured angular power-spectrum and degrades the $\fnl$ constraining power. The use of the nine maps more than doubles the uncertainty compared to using only the three primary maps in the regression. Our results thus motivate the development of more efficient methods that avoid over-correction, protect large-scale clustering information, and preserve constraining power. Additionally, our results encourage further studies of $\fnl$ with DESI spectroscopic samples, where the inclusion of 3D clustering modes should help separate imaging systematics and lessen the degradation in the $\fnl$ uncertainty.

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Measuring the conditional luminosity and stellar mass functions of galaxies by combining the DESI LS DR9, SV3 and Y1 data

In this investigation, we leverage the combination of Dark Energy Spectroscopic Instrument Legacy imaging Surveys Data Release 9 (DESI LS DR9), Survey Validation 3 (SV3), and Year 1 (Y1) data sets to estimate the conditional luminosity and stellar mass functions (CLFs & CSMFs) of galaxies across various halo mass bins and redshift ranges. To support our analysis, we utilize a realistic DESI Mock Galaxy Redshift Survey (MGRS) generated from a high-resolution Jiutian simulation. An extended halo-based group finder is applied to both MGRS catalogs and DESI observation. By comparing the r and z-band luminosity functions (LFs) and stellar mass functions (SMFs) derived using both photometric and spectroscopic data, we quantified the impact of photometric redshift (photo-z) errors on the galaxy LFs and SMFs, especially in the low redshift bin at low luminosity/mass end. By conducting prior evaluations of the group finder using MGRS, we successfully obtain a set of CLF and CSMF measurements from observational data. We find that at low redshift the faint end slopes of CLFs and CSMFs below $10^{9}h^{-2}L_{\odot}$ (or $h^{-2}M_{\odot}$) evince a compelling concordance with the subhalo mass functions. After correcting the cosmic variance effect of our local Universe following arXiv:1809.00523, the faint end slopes of the LFs/SMFs turn out to be also in good agreement with the slope of the halo mass function.

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AuriDESI: Mock Catalogues for the DESI Milky Way Survey

The Dark Energy Spectroscopic Instrument Milky Way Survey (DESI MWS) will explore the assembly history of the Milky Way by characterising remnants of ancient dwarf galaxy accretion events and improving constraints on the distribution of dark matter in the outer halo. We present mock catalogues that reproduce the selection criteria of MWS and the format of the final MWS data set. These catalogues can be used to test methods for quantifying the properties of stellar halo substructure and reconstructing the Milky Way's accretion history with the MWS data, including the effects of halo-to-halo variance. The mock catalogues are based on a phase-space kernel expansion technique applied to star particles in the Auriga suite of six high-resolution $Λ$CDM magneto-hydrodynamic zoom-in simulations. They include photometric properties (and associated errors) used in DESI target selection and the outputs of the MWS spectral analysis pipeline (radial velocity, metallicity, surface gravity, and temperature). They also include information from the underlying simulation, such as the total gravitational potential and information on the progenitors of accreted halo stars. We discuss how the subset of halo stars observable by MWS in these simulations corresponds to their true content and properties. These mock Milky Ways have rich accretion histories, resulting in a large number of substructures that span the whole stellar halo out to large distances and have substantial overlap in the space of orbital energy and angular momentum.

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Emission Line Predictions for Mock Galaxy Catalogues: a New Differentiable and Empirical Mapping from DESI

We present a simple, differentiable method for predicting emission line strengths from rest-frame optical continua using an empirically-determined mapping. Extensive work has been done to develop mock galaxy catalogues that include robust predictions for galaxy photometry, but reliably predicting the strengths of emission lines has remained challenging. Our new mapping is a simple neural network implemented using the JAX Python automatic differentiation library. It is trained on Dark Energy Spectroscopic Instrument Early Release data to predict the equivalent widths (EWs) of the eight brightest optical emission lines (including H$α$, H$β$, [O II], and [O III]) from a galaxy's rest-frame optical continuum. The predicted EW distributions are consistent with the observed ones when noise is accounted for, and we find Spearman's rank correlation coefficient $ρ_s > 0.87$ between predictions and observations for most lines. Using a non-linear dimensionality reduction technique (UMAP), we show that this is true for galaxies across the full range of observed spectral energy distributions. In addition, we find that adding measurement uncertainties to the predicted line strengths is essential for reproducing the distribution of observed line-ratios in the BPT diagram. Our trained network can easily be incorporated into a differentiable stellar population synthesis pipeline without hindering differentiability or scalability with GPUs. A synthetic catalogue generated with such a pipeline can be used to characterise and account for biases in the spectroscopic training sets used for training and calibration of photo-$z$'s, improving the modelling of systematic incompleteness for the Rubin Observatory LSST and other surveys.

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The MOST Hosts Survey: spectroscopic observation of the host galaxies of ~40,000 transients using DESI

We present the MOST Hosts survey (Multi-Object Spectroscopy of Transient Hosts). The survey is planned to run throughout the five years of operation of the Dark Energy Spectroscopic Instrument (DESI) and will generate a spectroscopic catalog of the hosts of most transients observed to date, in particular all the supernovae observed by most public, untargeted, wide-field, optical surveys (PTF/iPTF, SDSS II, ZTF, DECAT, DESIRT). Scientific questions for which the MOST Hosts survey will be useful include Type Ia supernova cosmology, fundamental plane and peculiar velocity measurements, and the understanding of the correlations between transients and their host galaxy properties. Here, we present the first release of the MOST Hosts survey: 21,931 hosts of 20,235 transients. These numbers represent 36% of the final MOST Hosts sample, consisting of 60,212 potential host galaxies of 38,603 transients (a transient can be assigned multiple potential hosts). Of these galaxies, 40% do not appear in the DESI primary target list and therefore require a specific program like MOST Hosts. Of all the transients in the MOST Hosts list, only 26.7% have existing classifications, and so the survey will provide redshifts (and luminosities) for nearly 30,000 transients. A preliminary Hubble diagram and a transient luminosity-duration diagram are shown as examples of future potential uses of the MOST Hosts survey. The survey will also provide a training sample of spectroscopically observed transients for photometry-only classifiers, as we enter an era when most newly observed transients will lack spectroscopic classification. The MOST Hosts DESI survey data will be released through the Wiserep platform on a rolling cadence and updated to match the DESI releases. Dates of future releases and updates are available through the https://mosthosts.desi.lbl.gov website.

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Constraints on the spacetime variation of the fine-structure constant using DESI emission-line galaxies

We present strong constraints on the spacetime variation of the fine-structure constant $α$ using the Dark Energy Spectroscopic Instrument (DESI). In this pilot work, we utilize $\sim110,000$ galaxies with strong and narrow O III $λλ$4959,5007 emission lines to measure the relative variation $Δα/α$ in space and time. The O III doublet is arguably the best choice for this purpose owing to its wide wavelength separation between the two lines and its strong emission in many galaxies. Our galaxy sample spans a redshift range of $0<z<0.95$, covering half of all cosmic time. We divide the sample into subsamples in 10 redshift bins ($Δz=0.1$), and calculate $Δα/α$ for the individual subsamples. The uncertainties of the measured $Δα/α$ are roughly between $2\times10^{-6}$ and $2\times10^{-5}$. We find an apparent $α$ variation with redshift at a level of $Δα/α=(2\sim3)\times10^{-5}$. This is highly likely to be caused by systematics associated with wavelength calibration, since such small systematics can be caused by a wavelength distortion of $0.002-0.003$ Å, which is beyond the accuracy that the current DESI data can achieve. We refine the wavelength calibration using sky lines for a small fraction of the galaxies, but it does not change our main results. We further probe the spatial variation of $α$ in small redshift ranges, and do not find obvious, large-scale structures in the spatial distribution of $Δα/α$. As DESI is ongoing, we will include more galaxies, and by improving the wavelength calibration, we expect to obtain a better constraint that is comparable to the strongest current constraint.

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Long-term follow-up observations of extreme coronal line emitting galaxies

We present new spectroscopic and photometric follow-up observations of the known sample of extreme coronal line emitting galaxies (ECLEs) identified in the Sloan Digital Sky Survey (SDSS). With these new data, observations of the ECLE sample now span a period of two decades following their initial SDSS detections. We confirm the nonrecurrence of the iron coronal line signatures in five of the seven objects, further supporting their identification as the transient light echoes of tidal disruption events (TDEs). Photometric observations of these objects in optical bands show little overall evolution. In contrast, mid-infrared (MIR) observations show ongoing long-term declines. The remaining two objects had been classified as active galactic nuclei (AGN) with unusually strong coronal lines rather than being TDE related, given the persistence of the coronal lines in earlier follow-up spectra. We confirm this classification, with our spectra continuing to show the presence of strong, unchanged coronal-line features and AGN-like MIR colours and behaviour. We have constructed spectral templates of both subtypes of ECLE to aid in distinguishing the likely origin of newly discovered ECLEs. We highlight the need for higher cadence, and more rapid, follow-up observations of such objects to better constrain their properties and evolution. We also discuss the relationships between ECLEs, TDEs, and other identified transients having significant MIR variability.

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Redshift evolution and covariances for joint lensing and clustering studies with DESI Y1

Galaxy-galaxy lensing (GGL) and clustering measurements from the Dark Energy Spectroscopic Instrument Year 1 (DESI Y1) dataset promise to yield unprecedented combined-probe tests of cosmology and the galaxy-halo connection. In such analyses, it is essential to identify and characterise all relevant statistical and systematic errors. In this paper, we forecast the covariances of DESI Y1 GGL+clustering measurements and characterise the systematic bias due to redshift evolution in the lens samples. Focusing on the projected clustering and galaxy-galaxy lensing correlations, we compute a Gaussian analytical covariance, using a suite of N-body and log-normal simulations to characterise the effect of the survey footprint. Using the DESI One Percent Survey data, we measure the evolution of galaxy bias parameters for the DESI Luminous Red Galaxy (LRG) and Bright Galaxy Survey (BGS) samples. We find mild evolution in the LRGs in 0.4 < z < 0.8, subdominant compared to the expected statistical errors. For BGS, we find less evolution effects for brighter absolute magnitude cuts, at the cost of reduced sample size. We find that with a fiducial redshift bin width delta z = 0.1, evolution effects on GGL is negligible across all scales, all fiducial selection cuts, all fiducial redshift bins, given DESI Y1 sample size. Galaxy clustering is more sensitive to evolution due to the bias squared scaling. Nevertheless the redshift evolution effect is insignificant for clustering above the 1-halo scale of 0.1Mpc/h. For studies that wish to reliably access smaller scales, additional treatment of redshift evolution is likely needed. This study serves as a reference for GGL and clustering studies using the DESI Y1 sample

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Redshift-dependent RSD bias from Intrinsic Alignment with DESI Year 1 Spectra

We estimate the redshift-dependent, anisotropic clustering signal in DESI's Year 1 Survey created by tidal alignments of Luminous Red Galaxies (LRGs) and a selection-induced galaxy orientation bias. To this end, we measured the correlation between LRG shapes and the tidal field with DESI's Year 1 redshifts, as traced by LRGs and Emission-Line Galaxies (ELGs). We also estimate the galaxy orientation bias of LRGs caused by DESI's aperture-based selection, and find it to increase by a factor of seven between redshifts 0.4 - 1.1 due to redder, fainter galaxies falling closer to DESI's imaging selection cuts. These effects combine to dampen measurements of the quadrupole of the correlation function caused by structure growth on scales of 10 - 80 Mpc/h by about 0.15% for low redshifts (0.4<z<0.6) and 0.8% for high (0.8<z<1.1). We provide estimates of the quadrupole signal created by intrinsic alignments that can be used to correct this effect, which is necessary to meet DESI's forecasted precision on measuring the growth rate of structure. While imaging quality varies across DESI's footprint, we find no significant difference in this effect between imaging regions in the Legacy Imaging Survey.

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DESI luminous red galaxy samples for cross-correlations

We present two galaxy samples, selected from DESI Legacy Imaging Surveys (LS) DR9, with approximately 20,000 square degrees of coverage and spectroscopic redshift distributions designed for cross-correlations such as with CMB lensing, galaxy lensing, and the Sunyaev-Zel'dovich effect. The first sample is identical to the DESI Luminous Red Galaxy (LRG) sample, and the second sample is an extended LRG sample with 2-3 times the DESI LRG density. We present the improved photometric redshifts, tomographic binning and their spectroscopic redshift distributions and imaging systematics weights, and magnification bias coefficients. The catalogs and related data products will be made publicly available. The cosmological constraints using this sample and Planck lensing maps are presented in a companion paper. We also make public the new set of general-purpose photometric redshifts trained using DESI spectroscopic redshifts, which are used in this work, for all galaxies in LS DR9.

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DESI Mock Challenge: Constructing DESI galaxy catalogues based on FastPM simulations

Together with larger spectroscopic surveys such as the Dark Energy Spectroscopic Instrument (DESI), the precision of large scale structure studies and thus the constraints on the cosmological parameters are rapidly improving. Therefore, one must build realistic simulations and robust covariance matrices. We build galaxy catalogues by applying a Halo Occupation Distribution (HOD) model upon the \textsc{FastPM} simulations, such that the resulting galaxy clustering reproduces high resolution $N$-body simulations. While the resolution and halo finder are different from the reference simulations, we reproduce the reference galaxy two-point clustering measurements -- monopole and quadrupole -- to a precision required by the DESI Year 1 Emission Line Galaxy sample down to non-linear scales, i.e. $k<0.5\,h\mathrm{Mpc}$ or $s>10\,\mathrm{Mpc}/h$. Furthermore, we compute covariance matrices based on the resulting \textsc{FastPM} galaxy clustering -- monopole and quadrupole. We study for the first time the effect of fitting on Fourier conjugate [e.g. power spectrum] on the covariance matrix of the Fourier counterpart [e.g. correlation function]. We estimate the uncertainties of the two parameters of a simple clustering model and observe a maximum variation of 20 per cent for the different covariance matrices. Nevertheless, for most studied scales the scatter is between two to ten per cent Consequently, using the current pipeline we can precisely reproduce the clustering of $N$-body simulations and the resulting covariance matrices provide robust uncertainty estimations against HOD fitting scenarios. We expect our methodology will be useful for the coming DESI data analyses and their extension for other studies.

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The DESI One-Percent Survey: A concise model for galactic conformity of ELGs

Galactic conformity is the phenomenon in which a galaxy of a certain physical property is correlated with its neighbors of the same property, implying a possible causal relationship. The observed auto correlations of emission line galaxies (ELGs) from the highly complete DESI One-Percent survey exhibit a strong clustering signal on small scales, providing clear evidence for the conformity effect of ELGs. Building upon the original subhalo abundance matching (SHAM) method developed by Gao et al. (2022, 2023), we propose a concise conformity model to improve the ELG-halo connection. In this model, the number of satellite ELGs is boosted by a factor of $\sim 5$ in the halos whose central galaxies are ELGs. We show that the mean ELG satellite number in such central halos is still smaller than 1, and the model does not significantly increase the overall satellite fraction. With this model, we can well recover the ELG auto correlations to the smallest scales explored with the current data (i.e. $r_{\mathrm{p}} > 0.03$ $\mathrm{Mpc}\,h^{-1}$ in real space and at $s > 0.3$ $\mathrm{Mpc}\,h^{-1}$ in redshift space), while the cross correlations between luminous red galaxies (LRGs) and ELGs are nearly unchanged. Although our SHAM model has only 8 parameters, we further verify that it can accurately describe the ELG clustering in the entire redshift range from $z = 0.8$ to $1.6$. We therefore expect that this method can be used to generate high-quality ELG lightcone mocks for DESI.

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GTC Follow-up Observations of Very Metal-Poor Star Candidates from DESI

The observations from the Dark Energy Spectroscopic Instrument (DESI) will significantly increase the numbers of known extremely metal-poor stars by a factor of ~ 10, improving the sample statistics to study the early chemical evolution of the Milky Way and the nature of the first stars. In this paper we report high signal-to-noise follow-up observations of 9 metal-poor stars identified during the DESI commissioning with the Optical System for Imaging and low-Intermediate-Resolution Integrated Spectroscopy (OSIRIS) instrument on the 10.4m Gran Telescopio Canarias (GTC). The analysis of the data using a well-vetted methodology confirms the quality of the DESI spectra and the performance of the pipelines developed for the data reduction and analysis of DESI data.

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Mitigating the noise of DESI mocks using analytic control variates

In order to address fundamental questions related to the expansion history of the Universe and its primordial nature with the next generation of galaxy experiments, we need to model reliably large-scale structure observables such as the correlation function and the power spectrum. Cosmological $N$-body simulations provide a reference through which we can test our models, but their output suffers from sample variance on large scales. Fortunately, this is the regime where accurate analytic approximations exist. To reduce the variance, which is key to making optimal use of these simulations, we can leverage the accuracy and precision of such analytic descriptions using Control Variates (CV). The power of control variates stems from utilizing inexpensive but highly correlated surrogates of the statistics one wishes to measure. The stronger the correlation between the surrogate and the statistic of interest, the larger the variance reduction delivered by the method. We apply two control variate formulations to mock catalogs generated in anticipation of upcoming data from the Dark Energy Spectroscopic Instrument (DESI) to test the robustness of its analysis pipeline. Our CV-reduced measurements offer a factor of 5-10 improvement in the measurement error compared with the raw measurements. We explore the relevant properties of the galaxy samples that dictate this reduction and comment on the improvements we find on some of the derived quantities relevant to Baryon Acoustic Oscillation (BAO) analysis. We also provide an optimized package for computing the power spectra and other two-point statistics of an arbitrary galaxy catalog as well as a pipeline for obtaining CV-reduced measurements on any of the AbacusSummit cubic box outputs. We make our scripts publicly available and report a speed improvement of $\sim$10 for a grid size of $N_{\rm mesh} = 256^3$ compared with \texttt{nbodykit}.

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