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H. Zou

Publications and source records attributed to H. Zou.

At least 37 records · Page 2Linked to original sources

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.

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The Linear Point Standard Ruler with DESI DR1 and DR2 Data

The linear point, a purely geometric feature in the monopole of the two-point correlation function, has been proposed as an alternative standard ruler. Compared to the peak in the correlation function, it is more robust to late-time nonlinear effects at the percent level. In light of improved simulations and high quality data, we revisit the robustness of the linear point and use it as an alternative to template-based fitting approaches typically used in BAO analyses. We present the linear point measurements on galaxy samples from the first and second data releases (DR1 and DR2) of the DESI survey. We convert the linear point into a dimensionless parameter $α_{iso,LP}$, defined as the ratio of the linear point in the fiducial cosmology and the observed value, analogous to the isotropic BAO scaling parameter $α_{iso}$ used in previous BAO measurements. Using the 2nd generation of AbacusSummit mock catalogs, we find that linear point measurements are more precise when calculated in the post-reconstruction regime with 15-60% smaller uncertainties than those pre-reconstruction. We find a systematic shift in the linear point measurements compared against the isotropic BAO measurements in mocks; we attribute this to the isotropic damping parameter responsible for smearing the linear point in the nonlinear regime. We propose a sample-dependent correction that mitigates the impact of late-time nonlinear effects. While this introduces a cosmology dependence in an otherwise model-independent measurement, this is necessary given the sub-percent precision dictated by current cosmological surveys. Comparing $α_{iso,LP}$ with isotropic BAO measurements made on the DESI DR1 and DR2 galaxy samples, we find excellent agreement after applying this correction, particularly post-reconstruction. We discuss future scope regarding cosmological inference with linear point measurements.

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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.

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Electron temperature relations and the direct N, O, Ne, S and Ar abundances of 49959 star-forming galaxies in DESI Data Release 2

We present the largest direct-method abundance catalogue of galaxies to date, containing measurements of 49959 star-forming galaxies at z < 0.96 from DESI Data Release 2. By directly measuring electron temperatures across multiple ionisation zones, we provide constraints on a number of electron temperature relations. Using the temperature measurements, we derive reliable abundances for N, O, Ne, S and Ar and measure the evolution of abundances and abundance ratios of as a function of metallicity and other galaxy properties. Our measurements include direct oxygen abundances for 49507 galaxies, leading to the discovery of the two most metal-poor galaxies in the nearby Universe, with oxygen abundances of 12+log(O/H) = $\rm 12+\log(O/H) = 6.77_{-0.03}^{+0.03}~\rm dex $ (1.2\% $\rm Z_{\odot}$) and $\rm 12+\log(O/H) = 6.81_{-0.04}^{+0.04}~\rm dex$ (1.3\% $\rm Z_{\odot}$). We identify a rare outlier population of 24 galaxies with high N/O ratios at low metallicity, reminiscent of galaxy abundances observed in the early Universe. We find the Ne/O ratio is constant at low metallicity but increases gradually at $\rm 12+log(O/H) > 8.105\pm0.004$ dex. We show that the S/O and Ar/O abundance ratios are strongly correlated, consistent with the expected additional Type Ia enrichment channel for S and Ar. In this work we present an initial survey of the key properties of the sample, with this dataset serving as a foundation for extensive future work on galaxy abundances at low redshift.

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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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The DESI DR1 Peculiar Velocity Survey: growth rate measurements from galaxy and momentum correlation functions

Joint analysis of the local peculiar velocity and galaxy density fields offers a promising route to testing cosmological models of gravity. We present a measurement of the normalised growth rate of structure, $fσ_8$, from the two-point correlations of velocity and density tracers from the DESI DR1 Peculiar Velocity and Bright Galaxy Surveys, the largest catalogues of their kind assembled to date. We fit the two-point correlation measurements with non-linear correlation function models, constructed from density and momentum power spectra generated using 1-loop Eulerian perturbation theory, and validate our methodology using representative mock catalogues. We find $fσ_8 = 0.391^{+0.080}_{-0.081}$, consistent to within $1σ$ with accompanying analyses of the same datasets using power spectrum and maximum-likelihood fields methods. Combining these growth rate results from different methods including appropriate correlations, we find a consensus determination $fσ_8(z = 0.07) = 0.4497 \pm 0.0548$, consistent with predictions from \textit{Planck}$+Λ$CDM cosmology. Jointly fitting to this consensus low-redshift growth rate and the DESI DR1 full-shape clustering dataset, we measure gravitational growth index $γ_{\rm L} = 0.580^{+0.110}_{-0.110}$, consistent with the prediction of general relativity.

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DESI DR2 Baryon Acoustic Oscillations from the Lyman Alpha Forest Multipoles

We present an alternative measurement of the Baryon Acoustic Oscillation (BAO) using the Legendre multipole representation of the Ly$α$ forest correlation functions from the second data release (DR2) of the Dark Energy Spectroscopic Instrument survey. Compressing the auto- and cross-correlation functions into Legendre multipoles yields a positive-definite covariance matrix without any smoothing -- unlike the baseline DR2 analysis -- thanks to a significantly reduced data vector size. We introduce the statistical corrections required to debias the finite-sample covariance matrix estimate and demonstrate that monopole and quadrupole terms for both auto- and cross-correlations can be used even when the correlation functions are distorted by continuum errors and contaminated by metals. This formalism has slightly diminished the constraining power of the BAO scale, while considerably weakening constraints on nuisance parameters. We measure the isotropic BAO scale with $0.93\%$ precision at $z_\mathrm{eff}=2.35$, the Hubble parameter $H(z_\mathrm{eff})=(239.5\pm3.4)~(147.09~\mathrm{Mpc}/r_d) ~\mathrm{km~s}^{-1}~\text{Mpc}^{-1}$, and the transverse comoving distance $D_M(z_\mathrm{eff})=(5.80 \pm 0.10)~(r_d/147.09~\mathrm{Mpc})$~Gpc for a given value of the sound horizon ($r_d$). Our BAO results are entirely consistent with the baseline DR2 analysis.

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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.

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Peering down the barrel with DESI DR2: 10 000+ inflows at $z$ < 0.6 reveal how galaxies accrete cold gas

Direct observational constraints on how galaxies acquire their gas remain remarkably limited, hindering our understanding of the baryon cycle. We present a search for down-the-barrel NaI D absorption towards 15.6 million galaxies at $z < 0.6$ in DESI Data Release 2. We use Bayesian evidence ratios to assess whether the absorption requires additional components tracing interstellar gas distinct from the systemic component of the galaxy. We construct a catalogue of 50 088 (27 420) galaxies with moderate (strong) evidence for down-the-barrel absorption. The inferred absorption components are broadly distributed in velocity, with approximately 50% at $v_{\rm flow} < -50$ km/s, 30% within 50 km/s of the systemic velocity and the remaining 20% at $v_{\rm flow} > 50$ km/s. We find strong evidence for a large population of low-velocity, infalling absorbers with velocities $\sim$20 km/s in edge-on galaxies, consistent with radial inflows predicted in simulations. The stronger correlation in early-type galaxies between inflow velocity and stellar velocity dispersion, compared to that with stellar mass, suggests that a portion of these inflows may be associated with accreting satellites. These results reveal the multiple pathways in which galaxies accrete gas at redshift $z < 0.6$ for the first time in a statistically significant sample.

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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.

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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.

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The DESI DR1 Peculiar Velocity Survey: global zero-point and $H_0$ constraints

The Dark Energy Spectroscopic Instrument (DESI) in its first Data Release (DR1) already provides more than 100,000 galaxies with relative distance measurements. The primary purpose of this paper is to perform the calibration of the zero-point for the DESI Fundamental Plane and Tully-Fisher relations, which allows us to measure the Hubble constant, $H_0$. This sample has a lower statistical uncertainty than any previously used to measure $H_0$, and we investigate the systematic uncertainties in absolute calibration that could limit the accuracy of that measurement. We improve upon the DESI Early Data Release Fundamental Plane $H_0$ measurement by a) using a group catalog to increase the number of calibrator galaxies and b) investigating alternative calibrators in the nearby Universe. Our baseline measurement calibrates to the SH0ES/Pantheon+ type Ia supernovae, and finds $H_0=73.7\pm 0.06\;(\text{stat.})\pm 1.1\;(\text{syst.})$ km s$^{-1}$ Mpc$^{-1}$. Calibrating to surface brightness fluctuation (SBF) distances yields a similar $H_0$. We explore measurements using other calibrators, but these are currently less precise since the overlap with DESI peculiar velocity tracers is much smaller. In future data releases with an even larger peculiar velocity sample, we plan to calibrate directly to Cepheids and the tip of the red giant branch, which will enable the uncertainty to decrease towards a percent-level measurement of $H_0$. This will provide an alternative to supernovae as the Hubble flow sample for $H_0$ measurements.

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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.

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Fiducial-Cosmology-dependent systematics for the DESI 2024 Full-Shape Analysis

We assess the impact of the fiducial cosmology choice on cosmological inference from full-shape (FS) fits of the galaxy power spectrum in the DESI 2024 Data Release 1 (DR1). Using a suite of AbacusSummit DR1 mock catalogues based on the Planck 2018 best-fit cosmology, we quantify potential systematic shifts introduced by analysing the data under five secondary cosmologies - featuring variations in matter density, thawing dark energy, higher effective number of neutrino species, reduced clustering amplitude, and the DESI DR1 BAO best-fit $w_0w_a$CDM cosmology - relative to DESI's baseline Planck 2018 cosmology. We investigate two complementary FS analysis approaches: full-modelling (FM) and ShapeFit (SF), each with distinct sensitivities to the assumed fiducial model. Across all tracers, we find for FM that systematic shifts induced by fiducial cosmology mismatches remain well below the DESI DR1 statistical uncertainties, with maximum deviations of 0.22$σ_\mathrm{DR1}$ in $Λ$CDM scenarios and 0.12$σ_\mathrm{DR1+SN}$ when including SN Ia mock data in extended $w_0w_a$CDM fits. For SF, the shifts in the compressed parameters remain below $0.45σ_\mathrm{DR1}$ for all tracers and cosmologies.

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Parity-odd Four-Point Correlation Function from DESI Data Release 1 Luminous Red Galaxy Sample

The parity-odd four-point function provides a unique probe of fundamental symmetries and potential new physics in the large-scale structure of the Universe. We present measurements of the parity-odd four-point function using the DESI DR1 LRG sample and assess its detection significance. Our analysis considers both auto- and cross-correlations, using two complementary approaches to the covariance: (i) the full analytic covariance matrix applied to the uncompressed data vector, and (ii) a compressed data vector combined with a hybrid covariance matrix constructed from simulations and analytic estimates. When using the full analytic covariance matrix without corrections, we observe apparent auto-correlation signals with significance up to $4σ$. However, this excess is also consistent with a mismatch between the statistical fluctuations estimated from the simulations and those present in the real data. Our findings therefore suggest that the parity-odd signal in the current DESI DR1 LRG sample is consistent with zero. We note, however, that the low completeness of this sample may have a non-negligible impact on the detection sensitivity. Future data releases with improved completeness will be crucial for further investigation.

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The DESI Y1 RR Lyrae catalog I: Empirical modeling of the cyclic variation of spectroscopic properties and a chemodynamical analysis of the outer halo

We present the catalog of RR Lyrae stars (RRLs) observed in the first year of operations of the Dark Energy Spectroscopic Instrument (DESI) survey. This catalog contains 6,240 RRLs out to $\sim120$\,kpc from the Galactic center and over 12,000 individual epochs with homogeneously-derived stellar atmospheric parameters. We introduce a novel methodology to model the cyclical variation of the spectroscopic properties of RRLs from single-epoch measurements. We employ this method to infer the systemic velocities and mean temperatures of fundamental and first-overtone mode RRLs in our sample (without distinguishing between individual spectral lines). For fundamental mode pulsators, we obtain radial velocity curves with amplitudes of $\sim$30--80\,km\,s$^{-1}$ and effective temperature curves with 300--1,000\,K variations, whereas for first-overtone pulsators these amplitudes are $\sim20$\,km\,s$^{-1}$ and $\sim 600$\,K, respectively. We use our sample to study the metallicity distribution of the halo and its dependence on Galactocentric distance ($R_{\rm GC}$). Using a radius-dependent mixture model, we split the data into chemodynamically distinct components and find that our inner halo sample ($R_{\rm GC}\lesssim50$\,kpc) is predominantly composed of stars with [Fe/H] $\sim-1.5$ and largely radial orbits (with an anisotropy parameter $β\sim0.94$), that we associate with the Gaia-Sausage-Enceladus merger. Stars in the halo field exhibit a broader and more metal-poor [Fe/H] distribution with more circular orbits ($β\sim0.39$). The metallicity gradient of the metal-rich and the metal-poor components is found to be $0.005$ and $0.010$\,dex\,kpc$^{-1}$, respectively. Our catalog highlights DESI's tantalizing potential for studying the Milky Way and the pulsation properties of RRLs in the era of large spectroscopic surveys.

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Inference of matter power spectrum at z=0 using DESI DR1 Full-Shape data

Measurements of galaxy distributions at large cosmic distances capture clustering from the past. In this study, we use a cosmological model to translate these observations into the present-day galaxy distribution. Specifically, we reconstruct the 3D matter power spectrum at redshift $ z = 0 $ using Dark Energy Spectroscopic Instrument (DESI) Year 1 (DR1) galaxy clustering data and Cosmic Microwave Background (CMB) observations, assuming the $ Λ\text{CDM} $ model, and compare it to the result assuming the $ w_0w_a \text{CDM} $ model. Building on previous state-of-the-art methods, we apply Effective Field Theory (EFT) modelling of the galaxy power spectrum to account for small-scale effects in the 2-point statistics of galaxy data. The EFT approach offers a more robust methodology than traditional methods for modelling the galaxy power spectrum from galaxy clustering data, which can be used to test the consistency of the assumed cosmological model. By incorporating both CMB and galaxy clustering data across a range of redshifts, we can identify discrepancies between the datasets, which would indicate potential inaccuracies in the assumed expansion history. While previous studies have shown consistency with $ Λ\text{CDM} $, this work extends the analysis with higher-quality data to further test the expansion histories of both $ Λ\text{CDM} $ and $ w_0w_a \text{CDM} $. Our findings show that both $ Λ\text{CDM} $ and $ w_0w_a \text{CDM} $ provide consistent fits to the matter power spectrum recovered from DESI DR1 data.

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Measurements of quasar proximity zones with the Ly$α$ forest of DESI Y1 quasars

The intergalactic medium (IGM) around quasars is shaped by their dense environments and by their excess ionizing radiation, forming a "quasar proximity zone" whose size and anisotropy depend on the quasar's halo mass, luminosity, age, and radiation geometry. Using over 10,000 quasar pairs from the Dark Energy Spectroscopic Instrument (DESI) Year 1 data, with projected comoving separations $r_{\perp} < 2\,h^{-1}{\rm Mpc}$, we investigate how the proximity zone of foreground quasars at $z\sim2{\rm-}3.5$ affects Lyman-alpha absorption in their background quasars. The large DESI sample enables unprecedented precision in measuring this "transverse proximity" effect, allowing a detailed investigation of the signal's dependence on the projected separation of quasar pairs and the luminosity of the foreground quasar. We find that enhanced gas clustering near quasars dominates over their ionizing effect, leading to stronger absorption on neighboring sightlines. Under the assumption that quasar ionizing luminosity is isotropic and steady, we infer the IGM overdensity profile in the vicinity of quasars, finding overdensities as high as $Δ\sim 10$ at comoving distance $\sim 1\,h^{-1}{\rm Mpc}$ from the most luminous systems. Surprisingly, however, we find no significant dependence of the proximity profile on the luminosity of the foreground quasar. This lack of luminosity dependence could reflect a cancellation between higher ionizing flux and higher gas overdensity, or it could indicate that quasar emission is highly time variable or anisotropic, so that the observed luminosity does not trace the ionizing flux on nearby sightlines.

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