arXiv subjects

S. Juneau

Publications and source records attributed to S. Juneau.

At least 19 recordsLinked to original sources

arXiv2026

Optical Depths from the Thermal Sunyaev-Zel'dovich Effect with ACT DR6 and DESI DR1 Spectroscopic Galaxies and Optically-Selected Clusters

We present stacked thermal Sunyaev-Zel'dovich (tSZ) effect measurements for three samples of galaxy groups and clusters: those traced by the Dark Energy Spectroscopic Intstrument Data Release 1 (DESI DR1) luminous red galaxies (LRG) and the DESI DR1 Bright Galaxy Sample (BGS), and an eROMaPPer optically-selected sample from the DESI Legacy Imaging Survey. We use the latest Atacama Cosmology Telescope DR6 (ACT)+Planck component-separated internal linear combination (ILC) Compton-$y$ maps and ACT+Planck coadded 90, 150, and 220 GHz temperature maps to extract the tSZ signal within a $\sim2'$ disk aperture for sources binned by luminosity, richness, or mass. We measure the average tSZ signal with high statistical significance, with signal-to-noise ratios surpassing 38 for LRG, 27 for BGS, and 39 for the eROMaPPer sample using the 90 GHz ACT DR6+Planck map. We conduct a detailed study of systematics and foregrounds such as dust and cosmic infrared background (CIB) contamination, which remain a core challenge for tSZ analysis. For the LRG and BGS samples, we find that dust and radio source emission dominate the tSZ signal at scales near and below the disk aperture radius. Large-scale ($R>4'$) contamination from the CIB is less significant. We mitigate these contaminants to isolate the tSZ signal and use a combination of simulated and real measurements to develop Compton-$y-$optical depth ($\bar y-\bar \tau$) scaling relations to infer optical depths, which are found to be in agreement with values measured using the pairwise kinematic SZ effect for the same tracer samples. The $\bar y-\bar \tau$ scaling relation for the eROMaPPer sample is the first such relationship to be derived directly from SZ measurements.

astro-ph.CO↗

arXiv2026

Sizing the Universe with DESI Galaxy Sizes: Plain Fundamentals of Fundamental-Plane Lensing

Weak gravitational lensing provides a powerful way to map cosmic structure, but most current measurements rely on galaxy shape distortions from deep imaging surveys and are affected by systematics such as intrinsic alignments, photometric-redshift uncertainties and shape-measurement biases. Here we present a spectroscopic galaxy-galaxy lensing magnification measurement using Fundamental-Plane (FP) size residuals, $\delta_r\equiv\Delta\log_{10}R_\mathrm{e}$, from 3.26 million DESI luminous red galaxy (LRG) sources behind DESI Bright Galaxy Survey lenses. The FP-like relation predicts the intrinsic sizes of LRGs from lensing-invariant quantities, including velocity dispersion $\sigma_0$ and surface brightness $I_\mathrm{e}$, with a scatter of about 0.06-0.07 dex. Lensing magnifies LRG sizes, giving the direct convergence response $\delta_r(\kappa)=\kappa/\ln 10$, but we show that the full lensing response is modified by magnification bias, because fitting $R_\mathrm{e}$ with $I_\mathrm{e}$ inevitably induces a magnitude dependence in $\bar{\delta}_r(m)$. After calibrating this response, we recover surface-density profiles with uncertainties comparable to those from individual Stage-III shear surveys using 5-20 million higher-redshift sources. The corresponding excess surface-density profiles agree with shear-based measurements. We further show that the estimator is robust to size-measurement uncertainties, with a convergence multiplicative bias only $\simeq -0.2$ times the size bias. FP lensing therefore provides a clean, spectroscopic and complementary probe of cosmic structure.

astro-ph.CO↗

arXiv2026

A Finely-Binned Measurement of the Connected Even-Parity Galaxy 4-Point Correlation Function of DESI Year 1 Luminous Red Galaxies

We present the connected even-parity galaxy 4-Point Correlation Function (4PCF) of DESI Year 1 (Y1) Luminous Red Galaxies (LRGs). This is one of the first measurements of the connected 4PCF on data, and shows a clear detection at $\sim$12 to 17$\sigma$ in the full-sky analysis. We test the robustness of the signal by varying three factors: hemisphere (north vs. south), redshift range (either the full range $0.4 < z < 1.1$ or the higher-number-density interval $0.4 < z < 0.8$), and sample completeness (the full sample vs. only the most complete regions within the number density-motivated cut). Finally, we cross-correlate different patches that are spatially well-separated, and thus should have largely independent noise. This approach, at leading order, is able to remove mismatch between the covariance matrix of the data and that of the mocks; however, in certain cases at the cost of sensitivity. We find $\sim$15$\sigma$ evidence for an even-parity 4PCF in this approach. Overall, the studies of the 4PCF presented here probe sensitively any mismatch between mock catalogs and data, and also open up the prospect of fitting a model, constraining cosmological parameters and galaxy biases, and searching for Baryon Acoustic Oscillation (BAO) features.

astro-ph.CO↗

arXiv2026

Extending the Stellar-to-Halo Mass Relation to Dwarf Galaxies with DESI DR1

Constraining the dark matter halos of the smallest galaxies offers fundamental insights into the nature of dark matter and stellar feedback. Using the Dark Energy Spectroscopic Instrument (DESI) Data Release 1, we infer the stellar-to-halo mass relation (SHMR) down to the dwarf scale ($M_\star < 10^9\,M_\odot$), without extrapolation from the higher mass range. Leveraging the unprecedented depth of the DESI Bright Galaxy Survey at $0.01 < z < 0.2$, we construct 12 samples spanning nearly four orders of magnitude in stellar mass, and measure their projected clustering $w_p$, galaxy-galaxy lensing $\Delta\Sigma$, as well as a novel observable: satellite occupation number $N_{\rm sat}$. The addition of $N_{\rm sat}$ enables robust subtraction of satellite contributions to both $w_p$ and $\Delta\Sigma$ across the 12 individual halo occupation distribution analyses, yielding an average halo-to-stellar mass relation (HSMR) of $\log \langle M_h(M_\star) \rangle = 12.06 + 0.58\log(M_\star/10^{11}) + (M_\star/10^{11})^{0.73}$. Combining this HSMR with an observed stellar mass function, we constrain the SHMR across five orders of magnitude in halo mass, with the power-law slope steepening from $0.32 \pm 0.06$ above the Milky Way mass to $2.08 \pm 0.21$ in the dwarf regime. Interestingly, the scatter about the SHMR grows from $0.17 \pm 0.02$ dex at Milky Way-like scales to $0.68_{-0.33}^{+0.21}$ dex for systems comparable to the Large Magellanic Cloud, suggesting that smaller galaxies follow increasingly diverse evolutionary paths. Our work highlights the power of DESI in probing the galaxy-halo connection within the dwarf regime, offering an exciting avenue to bridge the gap between large-scale and near-field cosmologies in the future.

astro-ph.GA↗

arXiv2026

A Unified Tracer Analysis of DESI DR2 Baryon Acoustic Oscillations

We improve upon previous efforts to optimally combine overlapping galaxy samples in the DESI baryon acoustic oscillation analysis. By weighting each galaxy by its linear bias, overlapping galaxies are combined into a single, unified catalog, naturally avoiding double counting of cosmic volume and including all auto- and cross- information at the catalog level. Improvements over the previous effort include the addition of QSO out to $z=1.6$ to account for all overlapping DR2 tracers and redshift-dependent bias treatment to improve reconstruction. We report distance measurements using this unified tracer, and find them to be highly consistent with the baseline DR2 BAO analysis. We also test for tracer-dependent systematics within the DESI data, and find no evidence of tracer-dependent systematics within $0.8<z<1.6$. Finally, we take advantage of the unified tracer to rebin the analysis in redshift in order to more finely resolve the redshift-to-distance relation. Dynamical dark energy results on this finer redshift binning indicate that there is no missed feature in the expansion history in the redshifts $0.8<z<1.6$, and reproduces DESI's preference for an evolving dark energy equation of state.

astro-ph.CO↗

arXiv2026

Systematic uncertainties on DESI Tully-Fisher distances constrained with Integral Field Spectroscopy

The Tully--Fisher (TF) relation is an empirical tool for estimating distances to spiral galaxies. The Dark Energy Spectroscopic Instrument (DESI) Peculiar Velocity (PV) Survey uses \texttt{`tractor'} photometric position angles to place fibers along the galaxy's semi-major axis and infer maximum rotational velocities for $\approx$ 53,000 spirals. Systematic errors arise if the photometric PA differs from the kinematic PA from velocity fields. We quantify systematic uncertainties in DESI-TF distance estimates from photometric PAs and assess the impact of photometric--kinematic PA misalignments. We analyze 215 nearby galaxies from the PISCO and AMUSING surveys, estimating maximum rotational velocities at $0.4\,R_{26}$ for consistency with DESI-PV. Kinematic parameters are derived using \texttt{`PaFit'} from \texttt{`Cappellari Software'}. Global photometric parameters rely on Siena Galaxy Atlas SGA-2020 \texttt{`tractor'} data, with \texttt{`HostPhot'} as an alternative approach. Approximately $28\%$ of our sample exhibit photometric--kinematic PA misalignments $>10^\circ$. The median bias in distance is $\approx +1.98\,\mathrm{Mpc}$ with a skewed residual distribution of outliers. The overall distance standard deviation is $19.35\,\mathrm{Mpc}$, with misaligned galaxies showing twice the dispersion of aligned ones. The Mean Percentage Error is $2.8\% \pm 1.96$ (SE). High galaxy-to-galaxy scatter appears in DESI-TF distances, particularly for misaligned systems. Because DESI-TF targets lack kinematic PA measurements, we recommend a global fractional uncertainty of $\approx 3.5\%$. When kinematic information is available, aligned galaxies with offsets $<10^\circ$ are consistent with $\approx 1\%$ uncertainty, while strongly misaligned or incomplete systems warrant an upper threshold of $\approx 10\%$.

astro-ph.GA↗

arXiv2026

Lyman Break Galaxy selection and redshift measurement with supervised contrastive learning

Some of the next steps for high-precision cosmology lie within the high-redshift, high-density universe. Spectroscopic survey experiments such as the Dark Energy Spectroscopic Instrument (DESI)'s second phase DESI Run 2 will shift towards probing Lyman Break Galaxy (LBG) populations from z$\sim$2 to z$\sim$4.5. For this faint sample, spectroscopic redshift measurement and sample decontamination remains a challenge, even after target selection. We propose an approach based on supervised weighted contrastive learning, in order to both learn a redshift representation for spectra and decontaminate the sample from quasars and low redshift emission line galaxies. This strategy generalizes the contrastive learning loss approach with continuous relationship weights, such that the network simultaneously learns redshift and classification tasks. The model shows stronger outlier classification and comparable redshift identification performances when compared to the previous network used for DESI (a modified version of QuasarNET) on the same dataset. In particular, contrastive learning is well suited to the small, visually-inspected sample used for training and testing, especially given the multi-task nature of this work.

astro-ph.CO↗

arXiv2026

DESI DR2 Results IV: Alcock-Paczy\'nski Measurements from the Lyman Alpha Forest and Cosmological Constraints

We present Alcock-Paczy\'nski (AP) measurements from the full shape of Lyman-$\alpha$ (Ly$\alpha$) forest correlation functions measured from the second data release (DR2) of the Dark Energy Spectroscopic Instrument (DESI). Our measurements include information from the Ly$\alpha$ forest auto-correlation and its cross-correlation with quasars. We constrain the AP effect with $1\%$ precision at an effective redshift $z_\mathrm{eff}=2.33$, which is twice as tight as the Baryon Acoustic Oscillation (BAO) constraint from the same data. When using the joint Ly$\alpha$ AP and BAO results, we measure the ratios $D_\text{H}(z_\mathrm{eff})/r_\text{d}=8.600 \pm 0.066$ and $D_\text{M}(z_\mathrm{eff})/r_\text{d}=39.32 \pm 0.33$, where $D_\text{M}$ is the transverse comoving distance, $D_\text{H}$ is the Hubble distance, and $r_\text{d}$ is the sound horizon at the drag epoch. Assuming $\Lambda$CDM, Ly$\alpha$ forest measurements combined with a nucleosynthesis prior produce a constraint on the Hubble constant $H_0=66.5\pm1.3\,\mathrm{km\,s^{-1}\,Mpc^{-1}}$. The Ly$\alpha$ AP result corresponds to a matter fraction constraint $\Omega_\text{m}=0.325\pm0.018$ in $\Lambda$CDM, which is $1.4\sigma$ higher than DESI BAO. This impacts the DESI results relative to the Cosmic Microwave Background (CMB), slightly reducing their discrepancy from $2.4\sigma$ to $2.2\sigma$. We present updated constraints on extended models using the joint DESI DR2 BAO and Ly$\alpha$ forest full shape data, together with external data sets. When considering a time-evolving dark energy equation of state parametrized by $w_0$ and $w_a$, we find it is preferred over $\Lambda$CDM at $2.7\sigma$ for the combination of DESI and CMB data, and at $3.2\sigma$ when also including supernovae. With the new Ly$\alpha$ AP measurement, DESI provides its most precise anchor for the expansion history at $z > 1$ in the matter-dominated Universe.

astro-ph.CO↗

arXiv2026

Validation of the DESI DR2 Ly$\alpha$ forest full-shape analysis

We present the validation of the Dark Energy Spectroscopic Instrument (DESI) Data Release 2 (DR2) Lyman-$\alpha$ (Ly$\alpha$) forest full-shape analysis. This analysis combines three-dimensional Ly$\alpha$ forest auto-correlations and cross-correlations with quasars to extract information from both the baryon acoustic oscillation (BAO) feature and the broadband clustering signal, with primary emphasis on the Alcock-Paczynski (AP) measurement. Compared to the DESI DR1 analysis, the DR2 validation uses substantially larger and more realistic mock datasets, including CoLoRe 2LPT and AbacusSummit Ly$\alpha$ forest simulations. The modeling framework is also improved through analytic marginalization over small scales ($<10$ $h^{-1}$Mpc) and the impact of ultraviolet background fluctuations. The validation program was completed prior to unblinding and defines quantitative requirements for the cosmological parameters of interest, which are evaluated using hundreds of mock realizations. We further test the analysis through independent fits to the auto- and cross-correlations, multiple catalog splits, and a broad suite of analysis and modeling variations applied to both mocks and blinded observational data. We find that the BAO and AP parameters satisfy all validation requirements and remain stable across all tests. In contrast, mock studies reveal a significant bias in the inferred growth-rate parameter $f\sigma_8$, leading us to exclude this measurement from the final analysis. The consistency across mocks, data splits, and robustness tests demonstrates that the DR2 Ly$\alpha$ full-shape analysis provides a reliable and substantially improved broadband AP measurement over previous Ly$\alpha$ forest studies.

astro-ph.CO↗

arXiv2026

CoLoRe-2LPT: Lyman-$\alpha$ mock catalogues for the validation of DESI cosmological analyses

The Lyman-$\alpha$ (Ly$\alpha$) forest has become a crucial probe for studying the large-scale structure of the universe at high redshift ($z > 2$), providing powerful constraints on Baryon Acoustic Oscillations (BAO) and the full-shape (FS) clustering of matter. As a key ingredient for upcoming BAO and FS analyses, we present a new generation of fast cosmological Ly$\alpha$ mocks based on second-order Lagrangian perturbation theory (2LPT). These new mocks significantly improve upon previous log-normal approaches, both at accurately capturing small scale clustering and at recovering the non-linear broadening of the BAO peak. They are able to reproduce Ly$\alpha$ statistics within $10\%$ of the latest DESI measurement; including the Ly$\alpha$ bias and the redshift-space distortion $\beta$ parameter, mean transmitted flux, and 1D power spectrum. The corresponding quasar (QSO) clustering is also improved with respect to previous approaches, calibrated against high-resolution Abacus simulations, recovering the observational QSO linear bias to less than $5\%$ and improving redshift-space distortions via 2LPT velocities and the addition of Fingers-of-God effects. Furthermore, these mocks incorporate high column density systems and metal lines, allowing us to explore the effects and systematics induced by these astrophysical contaminants. This new set of mocks has been key for enhancing the modeling and validation of the DESI DR2 Ly$\alpha$ full shape cosmological analysis. This work provides a physically motivated and computationally efficient tool for simulating current and next-generation Ly$\alpha$ surveys and validating FS and BAO analysis.

astro-ph.CO↗

arXiv2026

Lyman-$\alpha$ forest holography: 3D predictions from 1D measurements

Cosmological analyses of Lyman-$\alpha$ forest clustering rely on either one-dimensional correlations along individual sightlines or three-dimensional correlations between different sightlines. Because these observables probe the matter distribution on very different scales, they have traditionally been analyzed independently. In this work, we bridge this gap using ForestFlow, an emulator trained on a suite of cosmological hydrodynamical simulations that provides a unified description of Lyman-$\alpha$ forest clustering from linear to nonlinear scales. This framework enables us to determine the range of three-dimensional clustering models compatible with the DESI one-dimensional flux power spectrum ($P_{\rm 1D}$). The resulting predictions successfully reproduce the large-scale clustering measured by the DESI BAO analysis and provide physically motivated priors on nonlinear clustering that are used in a companion paper presenting the full-shape analysis of the DESI DR2 Lyman-$\alpha$ forest. We validate our methodology using the large-volume, high-resolution hydrodynamical simulation ACCEL-2, demonstrating excellent agreement across the full range of scales considered. Finally, we combine constraints from the $P_{\rm 1D}$ and BAO analyses on the parameter combinations $b_\delta \sigma_8$ and $b_\eta f \sigma_8$, finding that the two probes provide comparable constraining power while exhibiting complementary parameter degeneracies. Our results establish a direct connection between one- and three-dimensional Lyman-$\alpha$ forest measurements through ForestFlow, an approach we term Lyman-$\alpha$ holography by analogy with the reconstruction of higher-dimensional structure from lower-dimensional information.

astro-ph.CO↗

arXiv2026

1000 cataclysmic variables identified from DESI spectroscopy

Most cataclysmic variables (CVs) are discovered when they have an outburst generating an inherent selection bias against CVs that rarely, or never, outburst. CVs discovered by virtue of their spectroscopic characteristics are particularly valuable to offset this bias and we have used an established machine-learning technique to assist in searching 98 966 000 spectra obtained by the Dark Energy Spectroscopic Survey (DESI) to find such CVs. DESI observations are much deeper than previous spectroscopic surveys and we have identified 1029 CVs, 221 of which are new including ten of the AM CVn subtype. We have spectroscopically confirmed 441 CV candidates and obtained 84 new or improved orbital periods. We present revised space density estimates based upon this new data. We have also added ten more to the eight known examples of an intriguing class of CVs which exhibit peculiar changes in accretion.

astro-ph.SR↗

arXiv2026

Beyond traditional emission-line diagnostics: using autoencoders to uncover active galactic nuclei in DESI spectra

The growing volume of spectroscopic data in modern surveys motivates data-driven approaches that complement traditional emission-line diagnostics for active galactic nuclei (AGN) identification. We present a machine learning framework that exploits the full optical spectrum using unsupervised representation learning within a semi-supervised classification scheme. We use the SPENDER autoencoder to compress DESI galaxy spectra into a low-dimensional latent space and classify sources through a k-d tree nearest-neighbor search. The model is trained on 50,222 DESI Main Survey spectra from the Guadalupe dataset and released as part of Data Release 1 (DR1), restricted to z <= 0.5. We validate the performance using labels derived from FastSpecFit's emission line measurements defining seven galaxy classes: AGN, broad-line (BL), composite, star-forming, passive, retired, and Other. The method achieves high accuracies for AGN (0.952) and broad-line AGN (0.965), reliably identifying these sources even in low signal-to-noise spectra and recovering AGN missed by standard single-diagnostic methods. Our classification metrics are benchmarked against traditional diagnostics, and we show they represent lower limits of the model's true performance. We also find that the learned latent space correlates with key galaxy properties such as stellar mass and star-formation rate, demonstrating that it captures physically meaningful information. These results show that unsupervised spectral representation learning, implemented within a semi-supervised classification framework, provides a scalable and effective approach for constructing more complete AGN catalogues for current and future spectroscopic surveys.

astro-ph.GA↗

arXiv2026

Weak Evolution of Cosmic Atomic Hydrogen over the Past 4.5 Billion Years

The cosmic star formation rate density (CSFRD) has declined sharply toward the present day, but the roles of the atomic and molecular gas reservoirs remain uncertain. We measure the cosmic HI density, $\Omega_{\mathrm{HI}}$, over $0<z<0.41$ by combining HI spectra from the Five-hundred-meter Aperture Spherical Telescope with optical spectroscopy from the Dark Energy Spectroscopic Instrument for $\sim2.5$ million galaxies across $\sim12,000\,{\rm deg}^2$. We measure a raw decrease in $\Omega_{\mathrm{HI}}$ by a factor of $1.35\pm0.10$ over the past 4.5 Gyr. Even after applying the conservative systematic corrections from our forward model, the inferred decline is only $1.12\pm0.10$ -- still far weaker than the CSFRD decline (a factor of 2.46). The molecular gas density, in contrast, is known to evolve more closely with star formation. At fixed stellar mass, the average HI gas fraction evolves by less than 0.2 dex, showing that the weak evolution is present across the galaxy population. These quantitative differences rule out rapid depletion of galaxy HI as the primary driver of the late-time CSFRD decline, and provide a stringent benchmark for models of gas accretion, phase conversion and star-formation regulation.

astro-ph.GA↗

arXiv2026

The largest sample of AGN outflows in dwarf galaxies using DESI DR1

In the last decade, the presence of active galactic nuclei (AGN) outflows and feedback in dwarf galaxies ($\mathrm{M_\ast}$<$10^{10}\mathrm{M}_\odot$) has gained ground over supernova (SN) feedback as the main mechanism regulating star formation. In this work, we perform the first systematic search for AGN outflows in dwarf galaxies using the Dark Energy Spectroscopic Instrument Data Release 1 (DESI DR1). From $\sim$ 7 million galaxies at z$<$0.45, we identify ionized outflows through the detection of broad components in the [OIII]$\lambda5007$\AA emission line. Galaxies are divided into dwarf and massive systems. Then, using emission-line diagnostic diagrams, we classify as star forming or AGN. We identify 1,502 AGN dwarf galaxies with outflow signatures. Comparing the distributions of star forming and AGN galaxies with outflows, we find that, among the 1,502 AGN dwarf galaxies with outflow signatures, AGN are the most likely drivers of the observed outflows in $\sim$83$\%$ of those with W$_{80}$ velocity $>250$ km s$^{-1}$. This constitutes the largest statistical sample of AGN outflows in dwarf galaxies to date. In massive galaxies, AGN dominance occurs above W$_{80}>350$ km s$^{-1}$. Therefore, two new velocity thresholds are proposed for identifying AGN-driven outflows in dwarf and massive galaxies. Besides, we find that outflows in dwarf galaxies are more likely to escape the dark matter halo than those in massive galaxies, allowing gas to be redistributed from the inner to the outer regions. This suggests that AGN outflows may have a major impact on dwarf galaxies.

astro-ph.GA↗

arXiv2026

DESI DR2 Reference Mocks: Clustering results from UCHUU ELGs and QSOs

High-redshift galaxy clustering provides a powerful probe of the growth of structure, testing models of dark matter, dark energy, and galaxy formation during the epoch when the Universe was rapidly evolving. Emission line galaxies (ELGs) and quasars (QSOs) are used as tracers of dark matter by the Dark Energy Spectroscopic Instrument (DESI) to probe this redshift regime. We present results from ELG and QSO mock catalogs created from the Uchuu N-body simulation and tuned to DESI Data Release 2 (DR2) clustering. Employing a modified subhalo abundance matching (SHAM) technique, we populate Uchuu halos and subhalos with QSOs between 0.8 < z < 2.1. For ELGs, we modify this method to select satellite galaxies with low velocities relative to their associated central halos, and populate a separate set of Uchuu halos and subhalos with ELGs between 0.8 < z < 1.6. In this paper, we reproduce the redshift evolution of number density and clustering statistics across the fitted range of scales. We also measure the large-scale clustering bias of both the data and mock samples. These results improve simulated lightcone construction from cosmological models and enhance our understanding of the galaxy-halo connection.

astro-ph.CO↗

arXiv2026

Quality Assessment of Spectroscopic Data Reduction Pipelines Using Artificial Intelligence: Scrutinizing Data Release 2 from the DESI Survey

Large spectroscopic surveys now collect data at a scale that makes traditional visual inspection impractical. We present an unsupervised pipeline for spectroscopic quality assessment that requires no labeled training data. The method combines Uniform Manifold Approximation and Projection for dimensionality reduction with Friends-of-Friends clustering to isolate anomalous spectra for targeted review. We apply this pipeline to 58,291,334 spectra across 14,199 tiles from DESI Data Release 2, processing each tile independently to produce a tile-level outlier catalog. In each tile, the pipeline separates a dense core of typical spectra from small, isolated components and singletons, yielding a total of 1,095,816 outlier candidates. The mean tile-level outlier fraction is about 1.96 percent overall, with values of 0.76 percent and 2.36 percent for the dark and bright main-survey programs, respectively. From the visual inspection of 391 outlier candidates from the dark and bright programs of the main survey, we find that 66.8 percent exhibit identifiable spectral anomalies consistent with known reduction and calibration effects. By contrast, only 4.1 percent carry a non-zero quality flag from the standard reduction pipeline. This shows that the method provides a complementary quality-assessment layer to existing pipeline diagnostics and recovers a substantial population of problematic spectra that standard diagnostics miss. Extrapolating to the main-survey catalog, we estimate that approximately 218,000 candidate outliers are free of identifiable reduction artifacts and may correspond to genuine atypical spectra in the context of DESI. The pipeline is scalable, reproducible, and directly comparable across successive data releases, making it a practical quality-assurance monitor for DESI and future multi-object spectroscopic surveys.

astro-ph.IM↗

arXiv2026

DESI Data Release 2 ELGs: Property-dependent subsamples, imaging systematics, and clustering

Using emission-line galaxies (ELGs) from the Dark Energy Spectroscopic Instrument (DESI) Data Release 2, we evaluate a property-dependent correction to imaging systematics. We derive systematic weights following the same linear regression method used for other DESI tracers, but do so separately on ELG subsamples to provide a physically-informed alternative to the fiducial, neural-network-based approach. In doing so, we show that the deeper imaging in the Dark Energy Survey (DES) footprint leads to a higher overall number density but a lack of targets with extreme $g-r$ and $r-z$ colors. ELGs in the DES region also show a distinct redshift distribution when subsampled by position in the $g-r$ vs. $r-z$ plane. To address these effects, we implement a separate treatment of the DES footprint within the DESI catalog production pipeline, which is generally well-motivated and, in some cases, imperative for accurate clustering measurements. With DES treated separately, we find that property-dependent systematic weights further mitigate spurious clustering signal in $\sim$10% of subsamples, while the fiducial scheme remains optimal for the full sample.

astro-ph.CO↗