Dark Energy Spectroscopic Instrument Research Articles

Efficient identification of broad absorption line quasars using dimensionality reduction and machine learning

Efficient identification of broad absorption line quasars using dimensionality reduction and machine learning

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

Abstract 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 $f_{\rm NL} = 34^{+24(+50)}_{-44(-73)}$ at 68 per cent(95 per cent) 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.

Emission line predictions for mock galaxy catalogues: a new differentiable and empirical mapping from DESI

Abstract 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 Hα, Hβ, [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 ρs > 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.

F(T) gravity after DESI Baryon acoustic oscillation and DES supernovae 2024 data

In this work, we investigate new constraints on f(T) gravity using the recent Baryon Acoustic Oscillation (BAO) data released by the Dark Energy Spectroscopic Instrument (DESI) and the Type Ia supernovae (SNIa) catalog from the full 5-years of the Dark Energy Survey Supernova Program (DES-SN5YR). The f(T) cosmological models considered are characterised by power law late-time accelerated expansion. Our results show that the combination DESI BAO +rd CMB Planck suggests a Bayesian preference for late-time f(T) cosmological models over ΛCDM, obtaining a value of H0=68.3−3.5+3.0 [km/s/Mpc] in agreement with SH0ES collaboration, however, due to a bigger uncertainty.

Low Surface Brightness Galaxies from BASS+MzLS with Machine Learning

From ∼5000 deg2 of the combination of the Beijing–Arizona Sky Survey and Mayall z-band Legacy Survey which is also the northern sky region of the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys, we selected a sample of 31,825 candidates of low surface brightness galaxies (LSBGs) with the mean effective surface brightness 24.2<μ¯eff,g<28.8 mag arcsec−2 and the half-light radius 2.″5 < r eff < 20″ based on the released photometric catalog and the machine learning model. The distribution of the LSBGs is bimodal in the g − r color, indicating the two distinct populations of the blue (g − r < 0.60) and red (g − r > 0.60) LSBGs. The blue LSBGs appear spiral, disk or irregular while the red LSBGs are spheroidal or elliptical and spatially clustered. This trend shows that the color has a strong correlation with galaxy morphology for LSBGs. In the spatial distribution, the blue LSBGs are more uniformly distributed while the red ones are highly clustered, indicating that red LSBGs preferentially populate a denser environment than the blue LSBGs. Besides, both populations have a consistent distribution of ellipticity (median ϵ ∼ 0.3), half-light radius (median r eff ∼ 4″) and Sérsic index (median n = 1), implying the dominance of the full sample by the round and disk galaxies. This sample has definitely extended the studies of LSBGs to a regime of lower surface brightness, fainter magnitude and broader other properties than the previously Sloan Digital Sky Survey-based samples.

Photometric Objects Around Cosmic Webs (PAC). VI. High Satellite Fraction of Quasars

Photometric Objects Around Cosmic Webs (PAC). VI. High Satellite Fraction of Quasars

Investigating cosmic homogeneity using multifractal analysis of the SDSS-IV eBOSS DR16 quasar catalogue

ABSTRACT We analyse the volume-limited subsamples extracted from the sixteenth data release of the Sloan Digital Sky Survey-IV (SDSS-IV) eBOSS quasar survey spanning a redshift interval of 0.8 &amp;lt; z &amp;lt; 2.2, to estimate the scale of transition to homogeneity in the Universe. The multifractal analysis used for this purpose considers the scaling behaviour of different moments of quasar distribution in different density environments. This analysis gives the spectrum of generalized dimension Dq, where positive values of q characterize the scaling behaviour in overdense regions and the negative ones in underdense regions. We expect fractal correlation dimension Dq(r) = 3, for a homogeneous, random point distribution in 3-Dimensions. The fractal correlation dimension Dq(r), corresponding to q = 2 obtained in our study stabilizes in the range (2.8–2.9) for scales r &amp;gt; 80 h−1 Mpc. The observed quasar distribution shows consistency with the simulated mock data and the random distribution of quasars within one sigma. Further, the generalized dimension spectrum Dq(r) also reveals transition to homogeneity beyond &amp;gt;110 h−1 Mpc, and the dominance of clustering at small scales r &amp;lt; 80 h−1 Mpc. Consequently, our study provides strong evidence for the homogeneity in SDSS quasar distribution, offering insights into large-scale structure properties and, thus can play a pivotal role in scrutinizing the clustering properties of quasars and its evolution in various upcoming surveys such as Dark Energy Spectroscopic Instrument and Extremely Large Telescope.

The DESI one-per cent survey: exploring the halo occupation distribution of luminous red galaxies and quasi-stellar objects with AbacusSummit

ABSTRACT We present the first comprehensive halo occupation distribution (HOD) analysis of the Dark Energy Spectroscopic Instrument (DESI) One-Percent Survey luminous red galaxy (LRG) and Quasi Stellar Object (QSO) samples. We constrain the HOD of each sample and test possible HOD extensions by fitting the redshift-space galaxy 2-point correlation functions in 0.15 &amp;lt; r &amp;lt; 32 h−1 Mpc in a set of fiducial redshift bins. We use AbacusSummit cubic boxes at Planck 2018 cosmology as model templates and forward model galaxy clustering with the AbacusHOD package. We achieve good fits with a standard HOD model with velocity bias, and we find no evidence for galaxy assembly bias or satellite profile modulation at the current level of statistical uncertainty. For LRGs in 0.4 &amp;lt; z &amp;lt; 0.6, we infer a satellite fraction of $f_\mathrm{sat} = 11\pm 1~{y{\ \mathrm{per\,cent}}}$, a mean halo mass of $\log _{10}\overline{M}_h/M_\odot =13.40^{+0.02}_{-0.02}$, and a linear bias of $b_\mathrm{lin} = 1.93_{-0.04}^{+0.06}$. For LRGs in 0.6 &amp;lt; z &amp;lt; 0.8, we find $f_\mathrm{sat}=14\pm 1~{{\ \mathrm{per\,cent}}}$, $\log _{10}\overline{M}_h/M_\odot =13.24^{+0.02}_{-0.02}$, and $b_\mathrm{lin}=2.08_{-0.03}^{+0.03}$. For QSOs, we infer $f_\mathrm{sat}=3^{+8}_{-2}\mathrm{per\,cent}$, $\log _{10}\overline{M}_h/M_\odot = 12.65^{+0.09}_{-0.04}$, and $b_\mathrm{lin} = 2.63_{-0.26}^{+0.37}$ in redshift range 0.8 &amp;lt; z &amp;lt; 2.1. Using these fits, we generate a large suite of high fidelity galaxy mocks, forming the basis of systematic tests for DESI Y1 cosmological analyses. We also study the redshift-evolution of the DESI LRG sample from z = 0.4 up to z = 1.1, revealling significant and interesting trends in mean halo mass, linear bias, and satellite fraction.

Testing the cosmological Poisson equation in a model-independent way

We show how one can test the cosmological Poisson equation by requiring only the validity of three main assumptions: the energy-momentum conservation equations of matter, the equivalence principle, and the cosmological principle. We first point out that one can only measure the combination M≡Ωm(0)μ, where μ quantifies the deviation of the Poisson equation from the standard one and Ωm(0) is the fraction of matter density at present. Then we employ a recent model-independent forecast for the growth rate f(z) and the expansion rate E(z) to obtain constraints on M for a survey that approximates a combination of the Dark Energy Spectroscopic Instrument (DESI) and Euclid. We conclude that a constant M can be measured with a relative error σM=4.5%, while if M is arbitrarily varying in redshift, it can be measured only to within 13.4% (1 σ c.l.) at redshift z=0.9, and 15-22% up to z=1.5. We also project our constraints on some parametrizations of M proposed in literature, while still maintaining model-independence for the background expansion, the power spectrum shape, and the non-linear corrections. Generally speaking, as expected, we find much weaker model-independent constraints than found so far for such models. This means that the cosmological Poisson equation remains quite open to various alternative gravity and dark energy models.

The frequency of metal enrichment of cool helium-atmosphere white dwarfs using the DESI early data release

ABSTRACT There is an overwhelming evidence that white dwarfs host planetary systems; revealed by the presence, disruption, and accretion of planetary bodies. A lower limit on the frequency of white dwarfs that host planetary material has been estimated to be ≃ 25–50 per cent; inferred from the ongoing or recent accretion of metals on to both hydrogen-atmosphere and warm helium-atmosphere white dwarfs. Now with the unbiased sample of white dwarfs observed by the Dark Energy Spectroscopic Instrument (DESI) survey in their Early Data Release (EDR), we have determined the frequency of metal enrichment around cool-helium atmosphere white dwarfs as 21 ± 3 per cent using a sample of 234 systems. This value is in good agreement with values determined from previous studies. With the current samples we cannot distinguish whether the frequency of planetary accretion varies with system age or host-star mass, but the DESI data release 1 will contain roughly an order of magnitude more white dwarfs than DESI EDR and will allow these parameters to be investigated.

Four Late-type Galaxies with Double Radio Lobes and Properties of Such Galaxies

The triggering mechanism for radio lobes from late-type galaxies is not fully understood. More samples are desired for a thorough investigation and statistics. By utilizing the optical data from the newly released Dark Energy Spectroscopic Instrument imaging surveys and the radio sources from the NRAO VLA Sky Survey and the Faint Images of the Radio Sky at Twenty-centimeter, we identify four Late-type Galaxies with double Radio Lobes (LaGRLs): J0217−3645, J0947+6220, J1412+3723 and J1736+5108. Including previously known LaGRLs, we confirm the correlation between radio power P 1.4 GHz and stellar mass M * of host galaxies. Most (25/35) LaGRLs belong to the blue cloud galaxies, while the newly identified cases in this work are located within the region of the red sequence. We find a clear correlation between the differential radio power, i.e., the offset from the P 1.4 GHz − M * relation, and the galaxy color, indicating that bluer galaxies at a fixed M * tend to host more powerful radio lobes. Furthermore, the majority (31/36) of LaGRLs are either located in a galaxy group or displaying a disturbed morphology. We suggest that all of the galaxy mass, color and surrounding environment could play important roles in triggering radio lobes in late-type galaxies.

Alignments in the orientation of radio jets from AGN and their host galaxies

It is well established that active galactic nuclei (AGNs) play an important role in the evolution of galaxies. These AGNs can be linked to the accretion processes onto massive black holes and past merger events in their host galaxies, which may lead to different alignments of the jets with respect to the host galaxies. This paper presents a study of the position angle (PA) differences between radio and optical images of radio-AGNs based on the second data release (DR2) of the Low Frequency Array (LOFAR) Two-Meter Sky Survey (LoTSS), the Karl G. Jansky Very Large Array Faint Images of the Radio Sky at Twenty-Centimeters Survey (FIRST), the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys, and the Sloan Digital Sky Survey (SDSS). We assessed PA measurement biases in the data and classified the radio-AGNs based on the radio luminosity and infrared colour from the Wide-field Infrared Survey Explorer (WISE). This resulted in the largest sample of radio AGNs with reliable radio and optical PA measurements published to date, with a total of 3682 AGNs. The PA difference (dPA) distributions for the radio-AGN sample show a prominent minor-axis alignment tendency. Based on some simple assumptions, we simulated the projection effect to estimate the intrinsic jet--galaxy alignment. The observed dPA distribution can be well described by a two-component jet-alignment model in which one component is more aligned with the minor axis of the host galaxy than the other. The fitting results indicate that the jet alignment is dependent on radio luminosity and the shape of the host galaxies, with the jets being more likely to be aligned with the minor axis of the galaxy for lower radio luminosity and for optically more elongated radio-AGNs. The minor-axis alignment of the entire sample may suggest a coherent accretion model present in most AGN host galaxies, while a considerable number of luminous radio-AGNs with massive host galaxies might have undergone accretion ---according to the chaotic model--- or past merger events.

CSST large-scale structure analysis pipeline: I. Constructing reference mock galaxy redshift surveys

ABSTRACT In this paper, we set out to construct a set of reference mock galaxy redshift surveys (MGRSs) for the future Chinese Space-station Survey Telescope (CSST) observation, where subsequent survey selection effects can be added and evaluated. This set of MGRSs is generated using the dark matter subhaloes extracted from a high-resolution Jiutian N-body simulation of the standard lambda-cold dark matter cosmogony with Ωm = 0.3111, ΩΛ = 0.6889, and σ8 = 0.8102. The simulation has a box size of 1 h−1Gpc, and consists of 61443 particles with mass resolution $3.723 \times 10^{8} \:h^{-1}\rm M_\odot$. In order to take into account the effect of redshift evolution, we first use all 128 snapshots in the Jiutian simulation to generate a light-cone halo/subhalo catalogue. Next, galaxy luminosities are assigned to the main and subhalo populations using the subhalo abundance matching (SHAM) method with the DESI (Dark Energy Spectroscopic Instrument) z-band luminosity functions at different redshifts. Multiband photometries, as well as images, are then assigned to each mock galaxy using a 3D parameter space nearest-neighbour sampling of the DESI LS (Legacy Imaging Survey) observational galaxies and groups. Finally, the CSST and DESI LS survey geometry and magnitude limit cuts are applied to generate the required MGRSs. As we have checked, this set of MGRSs can generally reproduce the observed galaxy luminosity/mass functions within 0.1 dex for galaxies with L &amp;gt; 108 h-2 L⊙ (or M* &amp;gt; 108.5 h-2M⊙) and within 1σ level for galaxies with L &amp;lt; 108 h-2 L⊙ (or M* &amp;lt; 108.5 h-2 M⊙). Together with the CSST slitless spectra and redshifts for our DESI LS seed galaxies that are under construction, we will set out to test various slitless observational selection effects in subsequent probes.

The DESI One-percent Survey: Evidence for Assembly Bias from Low-redshift Counts-in-cylinders Measurements

We explore the galaxy-halo connection information that is available in low-redshift samples from the early data release of the Dark Energy Spectroscopic Instrument (DESI). We model the halo occupation distribution (HOD) from z = 0.1 to 0.3 using Survey Validation 3 (SV3; a.k.a., the One-Percent Survey) data of the DESI Bright Galaxy Survey. In addition to more commonly used metrics, we incorporate counts-in-cylinders (CiC) measurements, which drastically tighten HOD constraints. Our analysis is aided by the Python package, galtab, which enables the rapid, precise prediction of CiC for any HOD model available in halotools. This methodology allows our Markov chains to converge with much fewer trial points, and enables even more drastic speedups due to its GPU portability. Our HOD fits constrain characteristic halo masses tightly and provide statistical evidence for assembly bias, especially at lower luminosity thresholds: the HOD of central galaxies in z ∼ 0.15 samples with limiting absolute magnitude M r < −20.0 and M r < −20.5 samples is positively correlated with halo concentration with a significance of 99.9% and 99.5%, respectively. Our models also favor positive central assembly bias for the brighter M r < −21.0 sample at z ∼ 0.25 (94.8% significance), but there is no significant evidence for assembly bias with the same luminosity threshold at z ∼ 0.15. We provide our constraints for each threshold sample’s characteristic halo masses, assembly bias, and other HOD parameters. These constraints are expected to be significantly tightened with future DESI data, which will span an area 100 times larger than that of SV3.

Primordial non-Gaussianities with weak lensing: information on non-linear scales in the Ulagam full-sky simulations

Primordial non-Gaussianities (PNGs) are signatures in the density field that encode particle physics processes from the inflationary epoch. Such signatures have been extensively studied using the Cosmic Microwave Background, through constraining their amplitudes, fX NL, with future improvements expected from large-scale structure surveys; specifically, the galaxy correlation functions. We show that weak lensing fields can be used to achieve competitive and complementary constraints. This is shown via the Ulagam suite of N-body simulations, a subset of which evolves primordial fields with four types of PNGs. We create full-sky lensing maps and estimate the Fisher information from three summary statistics measured on the maps: the moments, the cumulative distribution function, and the 3-point correlation function. We find that the year 10 sample from the Rubin Observatory Legacy Survey of Space and Time (LSST) can constrain PNGs to σ(f NL eq) ≈ 110, σ(f NL or, lss) ≈ 120, σ(f NL loc) ≈ 40. For the former two, this is better than or comparable to expected galaxy clustering-based constraints from the Dark Energy Spectroscopic Instrument (DESI). The PNG information in lensing fields is on non-linear scales and at low redshifts (z ≲ 1.25), with a clear origin in the evolution history of massive halos. The constraining power degrades by ∼60% under scale cuts of ≳ 20 Mpc, showing there is still significant information on scales mostly insensitive to small-scale systematic effects (e.g., baryons). We publicly release the Ulagam suite to enable more survey-focused analyses.

Redshift-dependent RSD bias from intrinsic alignment with DESI Year 1 spectra

ABSTRACT We estimate the redshift-dependent, anisotropic clustering signal in the Dark Energy Spectroscopic Instrument (DESI) 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. 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 (ξ2) caused by structure growth on scales of 10–80 h−1 Mpc by about 0.15 per cent for low redshifts (0.4 &amp;lt; z &amp;lt; 0.6) and 0.8 per cent for high (0.8 &amp;lt; z &amp;lt; 1.1), a significant fraction of DESI’s error budget. We provide estimates of the ξ2 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.

Changing-look Active Galactic Nuclei from the Dark Energy Spectroscopic Instrument. I. Sample from the Early Data

Changing-look active galactic nuclei (CL AGNs) can be generally confirmed by the emergence (turn-on) or disappearance (turn-off) of broad emission lines (BELs), associated with a transient timescale (about 100 ∼ 5000 days) that is much shorter than predicted by traditional accretion disk models. We carry out a systematic CL AGN search by crossmatching the spectra coming from the Dark Energy Spectroscopic Instrument and the Sloan Digital Sky Survey. Following previous studies, we identify CL AGNs based on Hα, Hβ, and Mg ii at z ≤ 0.75 and Mg ii, C iii], and C iv at z > 0.75. We present 56 CL AGNs based on visual inspection and three selection criteria, including 2 Hα, 34 Hβ, 9 Mg ii, 18 C iii], and 1 C iv CL AGN. Eight cases show simultaneous appearances/disappearances of two BELs. We also present 44 CL AGN candidates with significant flux variation of BELs, but remaining strong broad components. In the confirmed CL AGNs, 10 cases show additional CL candidate features for different lines. In this paper, we find: (1) a 24:32 ratio of turn-on to turn-off CL AGNs; (2) an upper-limit transition timescale ranging from 330 to 5762 days in the rest frame; and (3) the majority of CL AGNs follow the bluer-when-brighter trend. Our results greatly increase the current CL census (∼30%) and would be conducive to exploring the underlying physical mechanism.

Constraining the growth rate on linear scales by combining SKAO and DESI surveys

In the pursuit of understanding the large-scale structure of the Universe, the synergy between complementary cosmological surveys has proven to be a powerful tool. Using multiple tracers of the large-scale structure can significantly improve the constraints on cosmological parameters. We explore the potential of combining the Square Kilometre Array Observatory (SKAO) and the Dark Energy Spectroscopic Instrument (DESI) spectroscopic surveys to enhance precision on the growth rate of cosmic structures. We employ a multi-tracer Fisher analysis to estimate precision on the growth rate when using pairs of mock surveys that are based on SKAO and DESI specifications. The pairs are at both low and high redshifts. For SKA-MID, we use the HI galaxy and the HI intensity mapping samples. In order to avoid the complexities and uncertainties at small scales, we confine the analysis to scales where linear perturbations are reliable. The consequent loss of signal in each individual survey is mitigated by the gains from the multi-tracer. After marginalising over cosmological and nuisance parameters, we find a significant improvement in the precision on the growth rate.

A Large Sample of Extremely Metal-poor Galaxies at z < 1 Identified from the DESI Early Data

Extremely metal-poor galaxies (XMPGs) at relatively low redshift are excellent laboratories for studying galaxy formation and evolution in the early universe. Much effort has been spent on identifying them from large-scale spectroscopic surveys or spectroscopic follow-up observations. Previous work has identified a few hundred XMPGs. In this work, we obtain a large sample of 223 XMPGs at z < 1 from the early data of the Dark Energy Spectroscopic Instrument (DESI). The oxygen abundance is determined using the direct T e method based on the detection of the [O iii]λ4363 line. The sample includes 95 confirmed XMPGs based on the oxygen abundance uncertainty; the remaining 128 galaxies are regarded as XMPG candidates. These XMPGs are only 0.01% of the total DESI observed galaxies. Their coordinates and other properties are provided in the paper. The most XMPGs have an oxygen abundance of ∼1/34 Z ⊙, a stellar mass of about 1.5 × 107 M ⊙, and a star formation rate of 0.22 M ⊙ yr−1. The two most XMPGs present distinct morphologies suggesting different formation mechanisms. The local environmental investigation shows that XMPGs preferentially reside in relatively low-density regions. Many of them fall below the stellar mass–metallicity relations (MZRs) of normal star-forming galaxies. From a comparison of the MZR with theoretical simulations, it appears that XMPGs are good analogs to high-redshift star-forming galaxies. The nature of these XMPG populations will be further investigated in detail with larger and more complete samples from the ongoing DESI survey.

Optimal 1D Ly α forest power spectrum estimation – III. DESI early data

ABSTRACT The 1D power spectrum P1D of the Ly α forest provides important information about cosmological and astrophysical parameters, including constraints on warm dark matter models, the sum of the masses of the three neutrino species, and the thermal state of the intergalactic medium. We present the first measurement of P1D with the quadratic maximum likelihood estimator (QMLE) from the Dark Energy Spectroscopic Instrument (DESI) survey early data sample. This early sample of 54 600 quasars is already comparable in size to the largest previous studies, and we conduct a thorough investigation of numerous instrumental and analysis systematic errors to evaluate their impact on DESI data with QMLE. We demonstrate the excellent performance of the spectroscopic pipeline noise estimation and the impressive accuracy of the spectrograph resolution matrix with 2D image simulations of raw DESI images that we processed with the DESI spectroscopic pipeline. We also study metal line contamination and noise calibration systematics with quasar spectra on the red side of the Ly α emission line. In a companion paper, we present a similar analysis based on the Fast Fourier Transform estimate of the power spectrum. We conclude with a comparison of these two approaches and discuss the key sources of systematic error that we need to address with the upcoming DESI Year 1 analysis.