arXiv subjects

H. Zou

Publications and source records attributed to H. Zou.

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

The DESI Data Release 1 white dwarf catalogue

The Dark Energy Spectroscopic Instrument is conducting a redshift survey, mapping the universe in three dimensions to measure the history of cosmic expansion. As well as extragalactic objects, it is targeting millions of Milky Way stars, including white dwarfs. Using Data Release 1 we assemble the largest catalogue of spectroscopically-confirmed white dwarfs to date, whose straightforward selection function enables statistically-robust population studies. We visually inspect and fit models to spectra of 63968 objects, finding 44409 white dwarfs. We present their spectral classifications, atmospheric parameters and radial velocities. We assess survey completeness and uniformity, identify potential spectral contamination caused by flux from nearby sources entering the fibre, and assign confidence scores to our classifications to facilitate selection of statistical and observational samples. We present spectra representing most white dwarf classes, common and exotic. We conclude with recommendations and warnings regarding the use of the catalogue.

astro-ph.SR↗

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

Linking neutral gas inflows and outflows to offsets in the star-forming main sequence and mass-metallicity relation

Gas inflows and outflows regulate galaxy growth, but direct observational links between measured gas flows and galaxy scaling relations remain limited. Using ~6,000 star-forming galaxies with down-the-barrel Na I D absorption from DESI DR2, we examine how systems with detected neutral-gas inflows and outflows populate the star-forming main sequence (SFMS) and mass-metallicity relation (MZR). Inflow and outflow hosts are compared with stellar-mass- and redshift-matched controls, and with SFMS and MZR fits derived from galaxies without detected gas flows. Outflow hosts (v_flow $\leq$ -50 km s$^{-1}$) show enhanced sSFRs by 0.25-0.40 dex and elevated central metallicities by 0.04-0.06 dex in the lower-redshift sample. Slow inflow hosts (0 $<$ v_flow $<$ 100 km s$^{-1}$) show similarly enhanced sSFRs of 0.20-0.30 dex, but no significant metallicity offset, while fast inflow hosts (v_flow $\geq$ 100 km s$^{-1}$) show weaker SFR enhancement and modestly lower metallicities. Together, these trends support a regulator picture in which neutral gas flows trace different phases of the baryon cycle. Slow inflow hosts lie above the SFMS, consistent with accretion sustaining enhanced star formation without strong central metallicity dilution. This may indicate that inflowing gas is already metal-enriched or has mixed or enriched over extended timescales. By contrast, outflow hosts lie near the upper 1{$\sigma$} SFMS envelope, consistent with feedback regulating subsequent growth. Gas-flow hosts also show small but systematic offsets in the narrow 4000 {\AA} break strength ($D_n$4000) relative to controls matched in redshift, stellar mass and SFR. Our results show that neutral gas flows are associated with population-level offsets from the SFMS and MZR, consistent with a baryon-cycle contribution to scaling-relation scatter.

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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 $\approx 10\%$.

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arXiv2026

Improved constraints on the Milky Way potential using the M68 stream and DESI spectroscopic data

We present a selection of stars belonging to the stellar stream of the M68 (NGC 4590) globular cluster, also known as Fj\"orm. This star selection is an improvement on previous ones that used only Gaia data, as it incorporates spectroscopic measurements from the DESI survey and photometric data from the DESI Legacy Surveys. The selection contains 96 stars, each with five phase-space parameters from Gaia-DR3 and radial velocity from DESI, covering the entire observed section of the stream. This constitutes the largest selection of M68 stream stars with measured radial velocities to date. The observed stream is wider than expected from N-body simulations, and the stars farthest from the centre of the stream appear to be correlated in radial velocity space. This suggests that these stars cannot have been stripped from the cluster in a static axisymmetric potential. By modelling a mock sample of stream stars created using an N-body simulation, we found that we could reliably constrain the disc mass $M_{\rm d}$ and the dark matter halo axis ratio $q_{\rm h}$ of the Milky Way. This is because the stream flows close to and almost parallel to the disc. Using the 44 stars that are consistent with having been stripped from the cluster, combined with measurements of the Milky Way's rotation curve, we constrain the Galactic potential, obtaining $M_{\rm d} = 5.34 \pm 0.57 \times 10^{10}$ M$_{\rm sun}$ and an oblate halo of $q_{\rm h} = 0.83^{+0.06}_{-0.05}$. Additionally, by fitting the stream track, we estimate the Heliocentric distance of M68 to be $r=10.55\pm0.09$ kpc.

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

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

First planetesimals from DESI DR1: 12 highly metal-rich white dwarfs

Metal-enriched white dwarfs provide a unique insight into the composition of exoplanet interiors. These stars accrete the debris of disrupted planetary bodies, and hence, measuring the stellar parameters and photospheric abundances yields the bulk compositions of the parent bodies. At present, over 1750 debris-accreting white dwarfs are known, but just a few dozen are sufficiently enriched to allow a detailed abundance study. Here we report the analysis of 12 highly metal-enriched white dwarfs observed within the Data Release~1 of the Dark Energy Spectroscopic Instrument (DESI). We characterised their stellar parameters and photospheric metal abundances and we identified between three and ten different elements in their optical spectra, including most of the rock-forming species: O, Mg, Si, Ca and Fe. We conclude that the accreted bodies broadly resemble compositions found within the inner Solar System such as primitive meteorites, processed material or planetary cores. Six of the systems allowed a more thorough analysis: four of the parent bodies are composed of dry rock-forming elements; and two of them of something akin to a water-rich planetesimal. Thus, this study establishes DESI as a potent survey for identifying metal-rich targets, yielding reliable compositions of accreted exoplanetary material.

astro-ph.EP↗

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.

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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

Measuring local primordial non-Gaussianity from the clustering of DESI DR1 LRGs and QSOs

We report the first measurement of primordial non-Gaussianity (PNG), parameterized by $f_{\mathrm{NL}}$, in the configuration space two-point correlation function (2pcf). We employ simulation based modeling and a novel approach for the mitigation of imaging systematics. We apply this method to samples of luminous red galaxies (LRG) and quasars (QSO) observed by the Dark Energy Spectroscopic Instrument (DESI) during the first year of its observations (DR1). The observed 68\% CL interval on $f_{\mathrm{NL}}$ is $-3^{+22}_{-21}$ using LRGs, and $ 0^{+17}_{-16}$ using QSOs. The joint measurement yields $f_{\mathrm{NL}} = -3^{+12}_{-12}$ at $\ [68\%]$ CL. Our pipeline imposes a Gaussian prior on the value of $p$ (which defines the PNG bias via the Universality relation), with $p_{\rm LRG} = 1.0 \pm 0.1$ and $p_{\rm QSO} = 1.6\pm 0.1$. The observed constraining power of DESI tracers significantly exceeds that of previous large-scale structure (LSS) surveys, and encouragingly, approaches the sensitivity of CMB probes of PNG.

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↗

arXiv2026

Joint Modeling of GD-1 and C-19 as Old Streams

DESI observational data for the GD-1 and C-19 streams are compared to stream simulations in an evolving multi-halo potential of a Milky Way-like galaxy based on a cosmological Milky Way-like simulation. The number of subhalos decreases with time and the subhalo-stream encounter velocities rise as the Galaxy and its disk build up their mass. The streams develop from star clusters inserted at $\simeq$1 Gyr after the Big Bang and evolved for 13 Gyr to their current orbital positions. The measured velocity widths of the streams are compared to the matched simulations. Streams in a CDM subhalo population provide the best match to the velocity width, on the average, with considerable scatter. Streams younger than $\simeq$12 Gyr in CDM subhalos are insufficiently hot. Streams in the same potentials but with populations of WDM 5.5 keV subhalos are not, on the average, heated to the observed velocity widths, although some of the realizations do reach the observed levels. The stream density power spectrum measured along the length of the DESI GD-1 sample agrees with the CDM stream simulations, with 1.3 to 2.3 times more power than WDM 7 keV and 5.5 keV simulations. The simulations show that modeling specific streams from the time of the formation of their progenitor clusters is both feasible and necessary to reproduce their stream averaged kinematic properties.

astro-ph.GA↗

arXiv2026

Mapping the nuclear environments of extreme coronal line emitting galaxies

Extreme coronal line emitters (ECLEs) are a rare class of galactic nuclei exhibiting unusually strong high-ionisation forbidden emission lines, and several ECLEs have been linked to tidal disruption events (TDEs). In this work, we compile and analyse optical spectra of 33 ECLEs, dividing them into variable, TDE-linked sources and non-variable, AGN-linked systems. Using multi-epoch spectroscopy from the Sloan Digital Sky Survey, Dark Energy Spectroscopic Instrument, and other facilities, we investigate the evolution of the emission line spectra and measure emission line profiles. Many variable ECLEs have changing spectra in which the highest-ionisation lines (e.g., [Fe X]-[Fe XIV]) appear and fade first, followed by [Fe VII], accompanied by brightening of [O III]. These changes may reflect a softening ionising continuum, the outward propagation of the ionisation front following the TDE flare, or both. Assuming virial motion, we translate line widths into characteristic radial distances, reconstructing the spatial distribution of line-emitting gas. Coronal lines are generally emitted at radii intermediate between the broad line region and the low-ionisation narrow line region. This ionisation stratification is seen in many sources, with similar incidence in variable and non-variable ECLEs, suggesting no apparent difference in circumnuclear gas distributions between active and quiescent nuclei. We find positive correlations between gas distance and black hole mass for both [O III] and [Fe VII]: the log(Distance)-log(Mass) relations have slopes $0.63\pm0.08$ and $0.69\pm0.12$, respectively, broadly consistent with a Mass$^{0.5}$ dependence and with characteristic radii set primarily by photoionisation.

astro-ph.GA↗

arXiv2026

A New Record Census of Dwarf AGN and a Bimodal $M_{\rm BH}$-$M_{\star}$ Scaling Relation with DESI DR1

Using the first spectroscopic data release from the Dark Energy Spectroscopic Instrument (DESI DR1), we search for AGN signatures in 1,678,787 low-redshift ($0.001 \le z \le 0.45$) line-emitting galaxies. Based on the [NII]-BPT emission-line ratio diagnostic, we identify AGN in 314,245/1,211,573 (25.9%) high-mass ($\log (M_{\star}/M_{\odot}) > 9.5$) and 9648/467,214 (2.1%) dwarf ($\log (M_{\star}/M_{\odot}) \le 9.5$) galaxies. Among these AGN, 17,949 are broad-line candidates (BL-AGN) with broad H$\alpha$ emission, enabling black hole (BH) mass estimates using single-epoch virial methods. We find that the AGN fraction in line-emitting galaxies increases monotonically with stellar mass, rising from $\sim$1.4% at the low-mass end to $\sim$93.3% at the high-mass end. Using the large BL-AGN sample, we extend the $M_{\rm BH} - M_{\star}$ scaling relation down to $\log (M_{\star}/M_{\odot}) \approx 7.8$ and $\log (M_{\rm BH}/M_{\odot}) \approx 4.4$. In the context of high-redshift overmassive BHs, our results suggest that galaxies and their central BHs may follow two distinct evolutionary pathways across cosmic time. With this paper, we release the EmFit value-added catalog, containing emission-line flux and width measurements for $\sim$7.4 million galaxies, the largest catalog with emission-line decomposition into narrow, broad, and outflow components to date. This work significantly expands upon the early DESI results and provides a statistical sample for probing the galaxy$-$BH connection in the low-mass galaxy regime.

astro-ph.GA↗