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Mahdi Qezlou

Publications and source records attributed to Mahdi Qezlou.

At least 19 recordsLinked to original sources

Small-scale Lyman alpha forest cosmology with PRIYA: Constraints from XQ100 and KODIAQ-SQUAD one-dimensional flux power spectra

We present a new cosmological analysis of the small-scale Lyman alpha forest 1D flux power spectrum (P1D) using high-resolution quasar spectra from XQ100 and KODIAQ-SQUAD, interpreted through the PRIYA emulator. PRIYA is a suite of galaxy formation simulations spanning a range of cosmological and inhomogeneous HeII reionization parameters, enabling few-percent-level predictions of the P1D. These datasets, probing down to $k \sim 6\,h\,\mathrm{Mpc}^{-1}$ at $z = 2-5$, offer access to non-linear scales inaccessible to large-volume surveys like eBOSS. We find that the XQ100 P1D yields constraints on the primordial power spectrum parameters $(A_P, n_P)$ at pivot scale $k_0 = 0.78\,\mathrm{Mpc}^{-1}$ that are consistent with PRIYA results from eBOSS DR14 and Planck CMB, albeit with broader uncertainties. Notably, this is achieved without external IGM temperature data, showing that XQ100 alone provides stronger constraints on thermal history than eBOSS DR14. In contrast, the KODIAQ-SQUAD P1D favors a significantly higher $A_P$ value, driven by the selection bias toward high-column density absorbers (HCDs). We also find that the P1D at $k > 0.045\,\mathrm{s/km}$ is more sensitive to Lyman limit system contamination and thermal history. When imposing a prior on $(A_P, n_P)$, the reduced $χ^2$ remains unchanged and the inferred mean IGM temperature is unaffected, suggesting that cosmological and thermal parameters are largely sensitive to different scales. The XQ100 P1D therefore provides complementary information on thermal nuisance parameters, which can be jointly fit with eBOSS or DESI P1D measurements to improve cosmological constraints.

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HETDEX Public Data Release 1: Source Catalog 2 and Data Cubes from ~90 sq deg of Integral-Field Optical Spectroscopy

The Hobby-Eberly Telescope Dark Energy Experiment (HETDEX) is a wide-field, integral-field spectroscopic survey designed to map the large-scale distribution of Lyman-alpha emitting galaxies (LAEs) at 1.88 < z < 3.52 and constrain dark energy at cosmic noon. Using the 10-m Hobby-Eberly Telescope and the Visible Integral-Field Replicable Unit (IFU) Spectrograph, HETDEX obtains >35,000 spectra per exposure over 3500-5500 Å at R~800 with ~1.8 arcsec image quality, enabling an untargeted census of emission-line galaxies across 540 sq deg. We present HETDEX Public Data Release 1 (PDR1), comprising 431,713 IFU observations covering 86.67 sq deg of noncontiguous sky in the Spring (13h, +51°) and Fall (1.5h, 0°) fields, along with legacy regions (COSMOS, GOODS-N, NEP, SA22). PDR1 includes the HETDEX Public Source Catalog 2 (HPSC2), an expanded and reprocessed version of Mentuch Cooper et al. (2023) incorporating four additional years of data, improved quality control, and new machine learning classifiers. HPSC2 contains 426,654 LAEs, 491,411 [O II] emitters, 19,457 low-z galaxies, 18,303 active galactic nuclei, and 150,608 stars, providing coordinates, redshifts or stellar velocities, and 1D spectra for each source. Because the data cubes use local sky subtraction optimized for faint emission-line detection, they are not suited for absolute surface-brightness measurements or very extended nearby galaxies. Appendix materials include the full detection catalog, the 1.6 million-candidate LAE sample, and raw detection databases. All products are publicly accessible through the HETDEX data portal (https://hetdex.org/data-results/), including access to a public JupyterLab. HPSC2 is also publicly available via Zenodo (DOI: 10.5281/zenodo.19581262).

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Enhancing Lyα Emitter Identification in HETDEX with a Convolutional Neural Network

We present a deep learning framework to enhance the identification of Ly$α$ emitters (LAEs) in the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX), an untargeted spectroscopic survey of LAEs at $1.9 < z < 3.5$ without imaging pre-selection. We primarily address the low signal-to-noise ratio (S/N) regime ($4.8 \leq \mathrm{S/N} \leq 5.5$), where LAE candidates suffer from substantial noise contamination. To distinguish LAE candidates from artifacts and sky residuals, we employ a convolutional neural network (CNN) trained on two-dimensional spectral images of single emission lines. The training sample is constructed from the HETDEX COSMOS catalog, with external validation from ancillary observations and our participatory science project, \textit{Dark Energy Explorers}. For small-format, low-resolution spectroscopic data, the model achieves a balanced accuracy, precision, and recall of $94.1\%$, $97.5\%$, and $97.5\%$, respectively, in the high-S/N regime ($\mathrm{S/N}>5.5$), and $85.1\%$, $78.2\%$, and $84.4\%$ in the low-S/N regime. Using HETDEX LAEs independently identified by DESI spectroscopy, the model recovers $99\%$ and $93\%$ of the high- and low-S/N LAEs, respectively. Visual attribution indicates that the CNN attends to smooth, spatially extended central emission in true positives and to irregular or noisy features in true negatives. Applied to the full HETDEX catalog, the CNN enables an S/N threshold down to 4.8 by suppressing spurious spikes across $z\sim 1.9$--$2.5$ in the redshift distribution. Our approach facilitates HETDEX cosmological analyses by mitigating false positives in galaxy clustering and highlights the value of domain-specific deep learning for refining low-S/N spectroscopic identification in untargeted surveys.

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Relatively Fast and Reasonably Furious: Evidence for Increased Burstiness in Smaller Halos at Cosmic Dawn

We introduce an effective framework to model star-formation burstiness and use it to jointly fit galaxy UV luminosity functions (UVLFs), clustering, and H$α$/UV ratios, providing the first robust empirical evidence that early galaxies hosted in lower-mass halos are burstier. Using $z\sim 4-6$ observations, we find that galaxies show approximately $0.6$ dex of SFR variability if hosted in halos of $M_h = 10^{11}\, M_\odot$ (typical of $M_{\rm UV}\approx -19$ galaxies at $z = 6$). This translates into a scatter of $σ_{M_{\rm UV}}\approx 0.75$ mag in the UVLF, in line with past findings. Strikingly, we find that burstiness grows for galaxies hosted in smaller halos, reaching $\gtrsim 1$ dex for $M_h \leq 10^{9}\, M_\odot$ (corresponding to $σ_{M_{\rm UV}} \approx 1.5$ mag for faint $M_{\rm UV} \gtrsim -15$ galaxies). Extrapolating to higher redshifts, when small halos were more prevalent, the inferred mass-dependent burstiness can reproduce observed UVLFs up to $z\sim 17$ within 1$σ$, potentially alleviating the tension between pre- and post-JWST galaxy-formation models. Current observations allow us to constrain the main burst timescale to approximately $20$ Myr, consistent with expectations from supernova feedback, and suggest broad distributions of ionizing efficiencies at fixed $M_{\rm UV}$. Our results demonstrate that mass-dependent burstiness, as predicted by hydrodynamical simulations, is critical for understanding the mass assembly of early galaxies.

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Ten-dimensional neural network emulator for the nonlinear matter power spectrum

We present GokuNEmu, a ten-dimensional neural network emulator for the nonlinear matter power spectrum, designed to support next-generation cosmological analyses. Built on the Goku $N$-body simulation suite and the T2N-MusE emulation framework, GokuNEmu predicts the matter power spectrum with $\sim 0.5 \%$ average accuracy for redshifts $0 \leq z \leq 3$ and scales $0.006 \leq k/(h\,\mathrm{Mpc}^{-1}) \leq 10$. The emulator models a 10D parameter space that extends beyond $Λ$CDM to include dynamical dark energy (characterized by $w_0$ and $w_a$), massive neutrinos ($\sum m_ν$), the effective number of neutrinos ($N_\text{eff}$), and running of the spectral index ($α_\text{s}$). Its broad parameter coverage, particularly for the extensions, makes it the only matter power spectrum emulator capable of testing recent dynamical dark energy constraints from DESI. In addition, it requires only $\sim $2 milliseconds to predict a single cosmology on a laptop, orders of magnitude faster than existing emulators. These features make GokuNEmu a uniquely powerful tool for interpreting observational data from upcoming surveys such as LSST, Euclid, the Roman Space Telescope, and CSST.

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Design and optimization of neural networks for multifidelity cosmological emulation

Accurate and efficient simulation-based emulators are essential for interpreting cosmological survey data down to nonlinear scales. Multifidelity emulation techniques reduce simulation costs by combining high- and low-fidelity data, but traditional regression methods such as Gaussian processes struggle with scalability in sample size and dimensionality. In this work, we present T2N-MusE, a neural network framework characterized by (i) a novel 2-step multifidelity architecture, (ii) a 2-stage Bayesian hyperparameter optimization, (iii) a 2-phase $k$-fold training strategy, and (iv) a per-$z$ principal component analysis strategy. We apply T2N-MusE to selected data from the Goku simulation suite, covering a 10-dimensional cosmological parameter space, and build emulators for the matter power spectrum over a range of redshifts with different configurations. We find the emulators outperform our earlier Gaussian process models significantly and demonstrate that each of these techniques is efficient in training neural networks or/and effective in improving generalization accuracy. We observe a reduction in the mean error by more than a factor of five and in the worst-case error by approximately a factor of eight in leave-one-out cross-validation, relative to previous work. This framework has been used to build the most powerful emulator for the matter power spectrum, GokuNEmu, and will also be used to construct emulators for other statistics in future.

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LATIS Data Release: $\sim4200$ Spectra of $z \sim 2-3$ Galaxies, Redshifts, and Intergalactic Medium Tomography Maps

We present the data release of the Ly$α$ Tomography IMACS Survey (LATIS), one of the largest optical spectroscopic surveys of faint high-redshift galaxies. The survey provides 7408 optical spectra of candidate $z \sim 2-3$ galaxies and QSOs in the Canada-France-Hawaii Telescope Legacy Survey D1, D2 (COSMOS), and D4 fields. The $R \sim 1000$ spectra were obtained using the Inamori Magellan Areal Camera and Spectrograph (IMACS) at the Magellan Baade telescope, with typical integrations of 12 hr. From these spectra, we measured 5575 high-confidence spectroscopic redshifts, of which 4176 are at $z > 1.7$, thereby substantially increasing the number of public spectroscopic redshifts at $z \approx 2-3$ in COSMOS and the other survey fields. The data release includes Ly$α$ transmission fluctuations measured in $4.7 \times 10^5$ pixels, which were used to create 3D maps of the intergalactic medium (IGM) transmission spanning 1.65 deg$^2$ and $z = 2.2-2.8$ at a resolution of 4 $h^{-1}$ cMpc. These are the largest such maps to date and provide a novel tracer of large-scale structure in legacy fields. We also provide ancillary data, including mock surveys. The LATIS data will enable a variety of community studies of galaxy evolution, environments, and the IGM around cosmic noon.

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LATIS: Galaxy-Environment Relations at Cosmic Noon and the Role of Sample Selection

We investigate the environmental dependence of galaxy properties at $z\sim2.5$ using the Ly$α$ Tomography IMACS Survey (LATIS), which provides high-resolution three-dimensional maps of intergalactic medium (IGM) overdensity via Ly$α$ forest tomography. Our analysis focuses on a UV-selected spectroscopic sample of 2185 galaxies from LATIS and a complementary set of 1157 galaxies from heterogeneous spectroscopic surveys in the COSMOS field. We compare these datasets to forward-modeled mock catalogs constructed from the IllustrisTNG300-1 simulation, incorporating realistic selection functions to match both LATIS and the literature sample. While the mass-complete simulation predicts strong environmental trends--more massive and quiescent galaxies preferentially occupy overdense regions--we find that such trends are significantly weaker or absent in the observed samples. The LATIS galaxies show no measurable correlation between specific star formation rate (sSFR) and IGM overdensity, a result reproduced by LATIS-like mock catalogs, confirming that UV selection systematically excludes passive and dusty galaxies in dense environments. The literature compilation, despite improved high-mass coverage, remains incomplete and affected by similar biases. We also analyze a mass-complete photometric sample from the COSMOS-Web catalog at $z\sim2.5$ and find no detectable sSFR-environment relation, a null result that our simulations indicate can be explained by photometric redshift uncertainties. In particular, we find no evidence for a reversal of the sSFR-density relation at cosmic noon. These results demonstrate that observed correlations can be heavily shaped by selection effects, and caution against inferring physical trends from incomplete spectroscopic samples. Deeper, more representative spectroscopic surveys are needed to robustly characterize environmental effects at this epoch.

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An AI super-resolution field emulator for cosmological hydrodynamics: the Lyman-α forest

We extend our super-resolution and emulation framework for cosmological dark matter simulations to include hydrodynamics. We present a two-stage deep learning model to emulate high-resolution (HR-HydroSim) baryonic fields from low-resolution (LR-HydroSim) simulations at redshift $z = 3$. The method takes as inputs an LR-HydroSim and the high-resolution initial conditions (HR-HydroICs). First, the model stochastically generates high-resolution baryonic fields from the LR-HydroSim. Second, a deterministic emulator refines these fields using HR-HydroICs to reconstruct small-scale structures including displacement, velocity, internal energy, and gas/star classification. Trained on paired low- and high-resolution simulations produced with \texttt{MP-Gadget}, the model captures small-scale structures of the intergalactic medium and %Lyman-$α$ forest observables down to the 100 kpc pressure smoothing scale relevant to the Lyman-$α$ forest. The model achieves subpercent error for overdensity, temperature, velocity, and optical depth fields, a mean relative error of 1.07\% in the large-scale flux power spectrum (\(k < 3 \times 10^{-2}\ \mathrm{s/km}\)), and less than 10\% error in the flux probability distribution function. Notably, the two-stage model reduces the compute time by a factor of $\sim$450 compared to full smoothed particle hydrodynamics at the same resolution. This work demonstrates the potential of this framework as a powerful and efficient tool for generating high-resolution fields offering fast and accurate alternatives to traditional cosmological hydrodynamic simulations and enabling large-volume mock datasets for next-generation cosmological surveys.

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The HETDEX Survey: Probing neutral hydrogen in the circumgalactic medium of ~88,000 Lyman Alpha Emitters

We explore the neutral hydrogen (H I) gas around 1.9 < z < 3.5 Lyman Alpha Emitters (LAEs) from the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX) using faint Ly$α$ absorption. This absorption is the result of H I in the halo of the LAE scattering Ly$α$ photons from the integrated light of background galaxies along the line of sight. We stack millions of spectra from regions around ~88,000 LAEs to focus on the physics of the gas at large radii. The extensive number of fiber spectra contributing to the stacks ensures significant signal-to-noise ratio (S/N) to detect the faint Ly$α$ absorption which would otherwise be buried within the noise. We detect absorption out to a projected ~350 kpc around an average LAE at z~2.5. We use these results to create an empirical radial $W_λ$(Ly$α$) profile around LAEs. Comparison with numerical simulations reveals a profile similar to the empirical one within this region. Compared to previous studies, the profile is similar but modestly higher. We also outline a simple physical picture motivated by the observed trends in the data. We plan to quantify this radial profile as a function of redshift, local density, and Ly$α$ luminosity to explore the relationship between LAE environments and H I distribution.

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LATIS: A Sample of IGM-selected Protoclusters and Protogroups at $z \sim 2.5$

The Ly$α$ Tomography IMACS Survey (LATIS) has produced large 3D maps of the intergalactic medium (IGM), providing a new window on the cosmic web at $z\sim2.5$. A key advantage of Ly$α$ tomography is that it enables the discovery of overdense regions without the need to detect their galaxy members in spectroscopic surveys, circumventing possible selection biases. We use these maps to identify 37 IGM-selected overdensities as regions of strong and spatially coherent Ly$α$ absorption. Simulations indicate that 85% of these are protoclusters, defined as the progenitors of $z=0$ halos with mass $M_{\rm desc} > 10^{14} M_{\odot}$, and that nearly all of the rest are protogroups ($10^{13.5} < M_{\rm desc} / M_{\odot} < 10^{14}$). We estimate the masses and space densities of the IGM-selected overdensities and show they are in accordance with mock surveys. We investigate the LATIS counterparts of some previously reported protoclusters, including the proto-supercluster Hyperion. We identify a new component of Hyperion beyond its previously known extent. We show that the Ly$α$ transmission of the galaxy density peaks within Hyperion is consistent with a simple physical model (the fluctuating Gunn-Peterson approximation), suggesting that active galactic nucleus feedback or other processes have not affected the large-scale gas ionization within this structure as whole. The LATIS catalog represents an order-of-magnitude increase in the number of IGM-selected protogroups and protoclusters and will enable new investigations of the connections between galaxies and their large-scale environments at cosmic noon.

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LATIS: Comparing Galaxy and IGM Tomography Maps as Tracers of Large-scale Structure and Protoclusters at $z \sim 2.5$

We investigate the consistency of intergalactic medium (IGM) tomography and galaxy surveys as tracers of the cosmic web and protoclusters at $z \sim 2.5$. We use maps from the Ly$α$ Tomography IMACS Survey (LATIS), which trace the distributions of Lyman-break galaxies (LBGs) and IGM Ly$α$ absorption on $\simeq 4$ $h^{-1}$ cMpc scales within the same large volume. Overall, the joint distribution of IGM absorption and LBG density is well constrained and accurately described by a simple physical model. However, we identify several exceptional locations exhibiting strong IGM absorption indicative of a massive protocluster, yet no coincident overdensity of LBGs. As discussed by Newman et al., whose results we revise using the complete LATIS survey data, these are candidate ultraviolet (UV)-dim protoclusters that may harbor distinct galaxy populations missed by rest-UV spectroscopic surveys. We present follow-up observations targeting one such candidate embedded within Antu, an extended region of IGM absorption at $z=2.685$ that contains five IGM-selected protoclusters and has a total mass of $3 \times 10^{15}~M_{\odot}$. Ly$α$ emitters trace the overall structure of Antu but avoid the center of the candidate UV-dim protocluster, which also appears to contain no submillimeter-selected sources. A near-infrared spectroscopic galaxy census is needed to determine whether this large region is dominated by galaxies with reduced or absent star-formation activity. This work adds to a growing and puzzling literature on discrepancies among different galaxy and IGM tracers, whose resolution promises to shed light on the early stages of environment-dependent galaxy evolution.

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Using Lyman Alpha Absorption to Measure the Intensity and Variability of $z \sim 2.4$ Ultraviolet Background Light

We present measurements of $z \sim 2.4$ ultraviolet background light using Lya absorption from galaxies at $z \sim 2-3$ in the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX) database. Thanks to the wide area of this survey, we also measure the variability of this light across the sky. The data suggest an asymmetric geometry where integrated ultraviolet light from background galaxies is absorbed by \ion{H}{1} within the halo of a foreground galaxy, in a configuration similar to damped Lya systems. Using stacking analyses of over 400,000 HETDEX LAE spectra, we argue that this background absorption is detectable in our data. We also argue that the absorption signal becomes negative due to HETDEX's sky subtraction procedure. The amount that the absorption is over-subtracted is representative of the $z \sim 2.4$ UV contribution to the overall extragalactic background light (EBL) at Lya. Using this method, we determine an average intensity (in $νJ_ν$ units) of $12.9 \pm 3.7$ nW m$^{-2}$ sr$^{-1}$ at a median observed wavelength of 4134 angstroms, or a rest-frame UV background intensity of $508 \pm 145$ nW m$^{-2}$ sr$^{-1}$ at $z\sim2.4$. We find that this flux varies significantly depending on the density of galaxies in the field of observation. Our estimates are consistent with direct measurements of the overall EBL.

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Forecast Cosmological Constraints with the 1D Wavelet Scattering Transform and the Lyman-$α$ forest

We make forecasts for the constraining power of the 1D Wavelet Scattering Transform (WST) when used with a Lyman-$α$ forest cosmology survey. Using mock simulations and a Fisher matrix, we show that there is considerable cosmological information in the scattering transform coefficients not captured by the flux power spectrum. We estimate mock covariance matrices assuming uncorrelated Gaussian pixel noise for each quasar, at a level drawn from a simple lognormal model. The extra information comes from a smaller estimated covariance in the first-order wavelet power, and from second-order wavelet coefficients which probe non-Gaussian information in the forest. Forecast constraints on cosmological parameters from the WST are more than an order of magnitude tighter than for the power spectrum, shrinking a $4D$ parameter space by a factor of $10^6$. Should these improvements be realised with DESI, inflationary running would be constrained to test common inflationary models predicting $α_s = - 6\times 10^{-4}$ and neutrino mass constraints would be improved enough for a $5-σ$ detection of the minimal neutrino mass.

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PRIYA: A New Suite of Lyman-alpha Forest Simulations for Cosmology

We present the PRIYA suite of cosmological simulations, based on the code and hydrodynamic model of the ASTRID simulation, and designed for cosmological analyses of the Lyman-$α$ forest. Our simulation suite spans a $9$-dimensional parameter space, including $4$ cosmological parameters and $5$ astrophysical/thermal parameters. We have run $48$ low fidelity simulations with $1536^3$ particles in a $120$ Mpc/h box and $3$ high fidelity simulations with $3072^3$ particles in a $120$ Mpc/h box. All our simulations include a full physics model for galaxy formation, including supernova and AGN feedback, and thus also contain a realistic population of DLAs. We advance on earlier simulations suites by larger particle loads, by incorporating new physical models for patchy hydrogen and helium reionization, and by self-consistently incorporating a model for AGN feedback. We show that patchy helium reionization imprints an excess in the 1D flux power spectrum on large scales, which may allow future measurements of helium reionization bubble sizes. Simulation parameters are chosen based on a Latin hypercube design and a Gaussian process is used to interpolate to arbitrary parameter combinations. We build a multi-fidelity emulator for the 1D flux power spectrum and the mean IGM temperature. We show that our final interpolation error is $< 1\%$ and that our simulations produce a flux power spectrum converged at the percent level for $z=5.4$ - $2.2$. Our simulation suite will be used to interpret Lyman-$α$ forest 1D flux power spectra from SDSS and future DESI data releases.

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Boosting Line Intensity Map Signal-to-Noise with the Ly-$α$ Forest Cross-Correlation

We forecast the prospects for cross-correlating future line intensity mapping (LIM) surveys with the current and future Ly-$α$ forest data. We use large cosmological hydrodynamic simulations to model the expected emission signal for the CO rotational transition in the COMAP LIM experiment at the 5-year benchmark and the Ly-$α$ forest absorption signal for various surveys, including eBOSS, DESI, and PFS. We show that CO$\times$Ly-$α$ forest can significantly enhance the detection signal-to-noise ratio of CO, with a $200$ to $300 \%$ improvement when cross-correlated with the forest observed in the Prime Focus Spectrograph (PFS) survey and a $50$ to $75\%$ enhancement for the currently available eBOSS or the upcoming DESI observations. We compare to the signal-to-noise improvements expected for a galaxy survey and show that CO$\times$Ly-$α$ is competitive with even a spectroscopic galaxy survey in raw signal-to-noise. Furthermore, our study suggests that the clustering of CO emission is tightly constrained by CO$\times$Ly-$α$ forest, due to the increased signal-to-noise ratio and the simplicity of Ly-$α$ absorption power spectrum modeling. Any foreground contamination or systematics are expected not to be shared between LIM surveys and Ly-$α$ forest observations; this provides an unbiased inference. Our findings highlight the potential benefits of utilizing the Ly-$α$ forest to aid in the initial detection of signals in line intensity experiments. For example, we also estimate that [CII]$\times$Ly-$α$ forest measurements from EXCLAIM and DESI/eBOSS, respectively, should have a larger signal-to-noise ratio than planned [CII]$\times$quasar observations by about an order of magnitude. Our results can be readily applied to actual data thanks to the observed quasar spectra in eBOSS Stripe 82, which overlaps with several LIM surveys.

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LATIS: Constraints on the Galaxy-halo Connection at $z \sim 2.5$ from Galaxy-galaxy and Galaxy-Ly$α$ Clustering

The connection between galaxies and dark matter halos is often quantified using the stellar mass-halo mass (SMHM) relation. Optical and near-infrared imaging surveys have led to a broadly consistent picture of the evolving SMHM relation based on measurements of galaxy abundances and angular correlation functions. Spectroscopic surveys at $z \gtrsim 2$ can also constrain the SMHM relation via the galaxy autocorrelation function and through the cross-correlation between galaxies and Ly$α$ absorption measured in transverse sightlines; however, such studies are very few and have produced some unexpected or inconclusive results. We use $\sim$3000 spectra of $z\sim2.5$ galaxies from the Lyman-alpha Tomography IMACS Survey (LATIS) to measure the galaxy-galaxy and galaxy-Ly$α$ correlation functions in four bins of stellar mass spanning $10^{9.2} \lesssim M_* / M_{\odot} \lesssim 10^{10.5}$. Parallel analyses of the MultiDark N-body and ASTRID hydrodynamic cosmological simulations allow us to model the correlation functions, estimate covariance matrices, and infer halo masses. We find that results of the two methods are mutually consistent and are broadly in accord with standard SMHM relations. This consistency demonstrates that we are able to accurately measure and model Ly$α$ transmission fluctuations $δ_F$ in LATIS. We also show that the galaxy-Ly$α$ cross-correlation, a free byproduct of optical spectroscopic galaxy surveys at these redshifts, can constrain halo masses with similar precision to galaxy-galaxy clustering.

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A population of ultraviolet-dim protoclusters detected in absorption

Galaxy protoclusters, which will eventually grow into the massive clusters we see in the local universe, are usually traced by locating overdensities of galaxies. Large spectroscopic surveys of distant galaxies now exist, but their sensitivity depends mainly on a galaxy's star formation activity and dust content rather than its mass. Tracers of massive protoclusters that do not rely on their galaxy constituents are therefore needed. Here we report observations of Lyman-$α$ absorption in the spectra of a dense grid of background galaxies, which we use to locate a substantial number of candidate protoclusters at redshifts 2.2-2.8 via their intergalactic gas. We find that the structures producing the most absorption, most of which were previously unknown, contain surprisingly few galaxies compared to the dark matter content of their analogs in cosmological simulations. Nearly all are expected to be protoclusters, and we infer that half of their expected galaxy members are missing from our survey because they are unusually dim at rest-frame ultraviolet wavelengths. We attribute this to an unexpectedly strong and early influence of the protocluster environment on the evolution of these galaxies that reduced their star formation or increased their dust content.

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