Eric Gawiser

Ly α emitters (LAEs) are star-forming galaxies with significant Ly α emission and are often used as tracers of large-scale structure at high redshift. We explore the relationship between the Ly α line profile and environmental density with spectroscopy from the Dark Energy Spectroscopic Instrument (DESI) of LAEs selected with narrowband photometry through the One-hundred-deg ² DECam Imaging in Narrowbands (ODIN) survey. We use LAE surface density maps in the N419 ( z ∼ 2.45) and N501 ( z ∼ 3.12) narrow bands to probe the relationship between local environmental density and the Ly α line profile. In both narrow bands, we stack the LAE spectra in bins of environmental density and inside and outside of protocluster regions. The N501 data show ∼15% higher Ly α line luminosity for galaxies in protoclusters, suggesting increased star formation in these regions. However, the line luminosity is not appreciably greater in protocluster galaxies in the N419 band, suggesting a potential redshift evolution of this effect. The shape of the line profile itself does not vary with environmental density, suggesting that line shape changes are caused by local effects independent of a galaxy’s environment. These data indicate a potential relationship between LAE local environmental density, ionized gas distribution, and Ly α line luminosity.

Context. Submillimeter galaxies (SMGs) are among the most intriguing and luminous objects in the high-redshift universe. These highly dusty star-forming systems provide valuable insights into galaxy formation and evolution and are likely affected by their cosmic environment. However, it is challenging to obtain large-area surveys with resolved SMGs and their spectroscopic redshifts. Aims. We quantify the environmental dependence of SMGs from z = 4 to z = 1 by assessing their preferential association with cosmic web structures (cluster-halo, filaments, and voids/walls) and evolution using the FLAMINGO simulation. Methods. We used the cosmic web finder DisPerSE to identify filamentary structures at redshifts z = 4, 3, 2, 1.5, and 1 in the highest-resolution FLAMINGO simulation using galaxies with M _∗ ≥ 10 ⁹ M _⊙ as tracers of large-scale structure. We defined five cosmic environments (inner cluster-halo, outer cluster-halo, inner filament, outer filament, and void/wall) at each redshift considering mass evolution of cluster-halos and density evolution of filaments. Results. The fraction of SMGs in the inner cluster-halo environment declines from ∼30% at z = 4 to ∼3% by z = 1, and similar trends are observed in other environments. The abundance of SMGs within a cluster-halo increases with halo mass and mirrors the increase in the total galaxy population. Consequently, the ratio of the SMG halo occupation to that of all galaxies is largely insensitive to halo mass, but varies with redshift. In contrast, the ratio of the halo occupation of non-SMGs to that of all galaxies declines with halo mass and shows little redshift evolution because star formation is suppressed in massive halos. We further show that SMGs tend to contribute less to the massive end of the stellar mass function in low-density environments, with central and satellite SMGs forming two distinct populations in the inner cluster-halos. SMGs occupy the metal-rich side of the star-forming gas metallicity distribution, but rarely attain the very highest metallicities because ongoing enrichment is limited by gas depletion. Interestingly, the brightest SMGs (S ₈₅₀ > 10 mJy) are found exclusively in inner cluster-halos, highlighting a strong connection between SMG luminosity and environmental density. Our results show that SMGs dominate star formation in dense environments, contributing up to 80% of the star formation rate in inner cluster-halos at z = 4, but less than 50% in low-density regions. Taken together, these results demonstrate that SMGs dominate the buildup of stellar mass and metals in dense environments, while their relative importance declines toward lower-redshift and lower-density regions.

We analyze the rest-frame optical (∼8000 Å) morphologies and star formation activity of Ly α emitters (LAEs) at redshifts 2.4, 3.1, and 4.5, identified in the One-hundred-deg ² DECam Imaging in Narrowband (ODIN) survey. To compare their physical properties with those of other galaxies, we construct a comparison sample of typical star-forming galaxies (SFGs) at similar redshifts from the COSMOS2025 catalog. Using James Webb Space Telescope NIRCam images from the COSMOS-Web survey, we measure the rest-frame optical sizes and Sérsic indices. We first examine their size–mass relations and find that LAEs at all three redshifts have smaller sizes than typical SFGs, with the size difference decreasing at higher redshifts. We also find that LAEs tend to have larger Sérsic indices at z = 2.4 and 3.1 than typical SFGs, but the difference becomes weaker at z = 4.5. These trends are qualitatively reproduced in the Horizon Run 5 cosmological hydrodynamical simulation. We then investigate star formation activity and find that LAEs exhibit higher star formation rates (SFRs) than typical SFGs at all redshifts considered. Finally, we examine the connection between Ly α emission and galaxy structure, finding that the rest-frame equivalent width (REW) of the Ly α emission line is negatively and positively correlated with size and Sérsic index, respectively. In addition, we find a strong positive correlation between Ly α REW and the ratio of the instantaneous SFR to that averaged over the last 100 Myr (i.e., SFR _inst /SFR _100Myr ). These results suggest the compact and starbursting nature of LAEs, and provide important constraints on the physical mechanisms responsible for Ly α photon escape from galaxies.

We present a detailed study of the 3D morphology of two extended associations of multiple protoclusters at z = 3.1. These protocluster “complexes,” designated COSMOS-z3.1-A and COSMOS-z3.1-C, are the most prominent overdensities of z = 3.1 Ly α emitters (LAEs) identified in the COSMOS field by the One-hundred-deg ² DECam Imaging in Narrowbands survey. These protocluster complexes have been followed up with extensive spectroscopy from Keck, Gemini, and DESI. Using a probabilistic method that combines photometrically selected and spectroscopically confirmed LAEs, we reconstruct the 3D structure of these complexes on scales of ≈50 cMpc. We validate our reconstruction method using the IllustrisTNG300-1 cosmological hydrodynamical simulation and show that it consistently outperforms approaches relying solely on spectroscopic data. The resulting 3D maps reveal that both complexes are irregular and elongated along a single axis, emphasizing the impact of sightline on our perception of structure morphology. The complexes consist of multiple density peaks, 10 in COSMOS-z3.1-A and 4 in COSMOS-z3.1-C. The former is confirmed to be a proto-supercluster, similar to Hyperion at z = 2.4 but observed at an even earlier epoch. Multiple “tails” connected to the cores of the density peaks are seen, likely representing cosmic filaments feeding into these extremely overdense regions. The 3D reconstructions further provide strong evidence that Ly α blobs preferentially reside in the outskirts of the highest density regions. Descendant mass estimates of the density peaks suggest that COSMOS-z3.1-A and COSMOS-z3.1-C will evolve to become ultramassive structures by z = 0, with total masses log ( M / M ⊙ ) ≳ 15.3 , exceeding that of Coma.

The One-hundred-deg ² DECam Imaging in Narrowbands (ODIN) survey is conducting the widest-field deep narrowband (NB) imaging of the equatorial and southern skies. ODIN uses three custom-built NB filters that sample Ly α -emitting galaxies (LAEs) within thin cosmic slices centered at z = 2.4, 3.1, and 4.5. In this work, we utilize extensive DESI spectroscopy of ODIN-selected galaxies in the COSMOS and XMM-LSS fields to validate our LAE selection. Exposures of 2–4 hr with DESI yielded redshift confirmation of 3075 ODIN LAE candidates with NB magnitudes brighter than 26 mag. Restricting to objects that yield high-confidence redshifts, the confirmation rates are (93%, 96%, 92%) at z = (2.4, 3.1, 4.5). The primary contaminants consist of active galactic nuclei at the expected Ly α- redshift range and lower redshifts (C iv , C iii ]), with the remainder being star-forming galaxies ([O ii ] and [O iii ]). We find minimal contamination from [O ii ] emitters in our sample (≲1%), implying that our rest-frame equivalent width (REW) > 20 Å NB excess photometry requirement is sufficient to remove them.

Protoclusters represent sites of accelerated galaxy formation and extreme astrophysical activity characteristic of dense environments. Identifying massive protoclusters and mapping their spatial structures are therefore crucial for understanding how large-scale environment influences galaxy evolution. We combine wide-field Ly α imaging from the One-hundred-deg ² DECam Imaging in Narrowbands survey with extensive Dark Energy Spectroscopic Instrument and ancillary spectroscopy across the extended COSMOS and XMM Large Scale Structure (LSS) fields (≈14 deg ² ) to search for massive protoclusters. We confirm six systems at z ≈ 2.4 and ≈ 3.1, including three newly identified structures and three which overlap with previously known structures and/or systems detected using other tracers. We reconstruct their three-dimensional structures, estimate descendant halo masses, and for one structure at z ≈ 3.12, demonstrate that overlapping narrowband filters (NB497 and N501) provide accurate redshift tomography for emission-line galaxies. One protocluster at z ≈ 2.45 overlaps with one of the LATIS tomographic fields, enabling direct comparison between galaxy and H i overdensities traced by Ly α forest absorption. Another at z ≈ 3.12 hosts a massive quiescent galaxy ( M _* ≈ 1.2 × 10 ¹¹ M _⊙ ), suggesting that overdense environments may play a role in accelerating galaxy assembly and quenching. Comparing Ly α emission properties across environments, we find that protocluster galaxies exhibit higher median line fluxes and a deficit of faint emitters relative to the field. The effect is strongest when combining 2D and 3D density information, indicating that galaxies in the densest protocluster cores are most affected by environmental processes. This effect is stronger at z ≈ 3.1 than at z ≈ 2.4, suggesting possible redshift evolution.

Spatially extended Ly α nebulae, known as Ly α blobs (LABs), are a rare population at z > 2 that are thought to trace protogroups or the progenitors of massive galaxies in the present-day Universe. However, their dark matter halo properties (e.g., halo mass) are still uncertain, due to their rarity and strong field-to-field variation. The One-hundred-deg ² DECam Imaging in Narrowbands (ODIN) survey has discovered 103 and 112 LABs in the extended (∼9 deg ² ) COSMOS field at z ∼ 2.4 and 3.1, respectively, enabling the estimation of their bias and host halo masses through clustering analysis. We measure the angular autocorrelation functions (ACFs) of the LABs and derive galaxy bias factors of b = 4.0 ± 0.8 and 3.8 ± 0.7, corresponding to minimum halo masses of 2 . 8 − 1.8 + 3.0 and 0 . 7 − 0.5 + 0.8 × 1 0 12 M _⊙ and median halo masses of 4 . 2 − 2.5 + 3.8 and 1 . 1 − 0.7 + 1.1 × 1 0 12 M _⊙ at z ∼ 2.4 and 3.1, respectively. LABs occupy ∼11 − 8 + 39 % and ∼3 − 2 + 9 % of all dark matter halos above these minimum halo masses. These findings suggest that LABs inhabit massive dark matter halos, likely tracing protogroup environments that evolve into present-day massive halos (∼10 ¹³ M _⊙ ), where massive elliptical galaxies or galaxy groups reside, by z = 0.

The galaxy–halo connection traces processes by which galaxies form and evolve. The halo occupation distribution (HOD) describes the relationship between galaxies and their host dark matter haloes. Measurements of the galaxy two-point correlation function (2PCF) allow us to extract information about the HODs of observed galaxy samples. Several parametric HOD models have been proposed in the literature, but the choice of parameterization restricts the space of possible HODs. To resolve this issue, we introduce a nonparametric HOD fitting method in which we train an emulator to learn the mappings among the galaxy 2PCF, physical properties used to select galaxy samples, and the HOD, all obtained from simulated past light cones constructed with the Santa Cruz semianalytic model. Implementing this emulator within a likelihood analysis framework, we derive constraints on the HOD of a galaxy sample when provided with a measurement of its 2PCF. Using the emulator to accelerate likelihood evaluations, we test the nonparametric HOD approach on a set of 2PCFs for mock galaxy samples drawn from the TNG100-1 simulation and selected above threshold values of stellar mass and star formation rate. Our framework is able to recover TNG100-1 HODs within 0.2 dex. We use the TNG100-1 mocks to tune the reported uncertainties to estimate those expected in the analysis of observations. Comparing to parametric HOD modelling routines applied to the same mock galaxy samples, our approach consistently infers the HOD with comparable or greater precision and accuracy.

The Legacy Survey of Space and Time (LSST) that will be carried out by the NSF-DOE Vera C. Rubin Observatory promises to be the defining survey of the next decade for both static and time-domain science. Maximizing the LSST’s scientific output requires a nontrivial survey strategy (i.e., the sequence of observations in space, time, and passband). For time-domain science, the most promising strategy to date is a rolling survey strategy, whereby alternating subsets of the full LSST area are observed at a higher-than-nominal rate. Focusing on static science (galaxy clustering and weak lensing), we study how time-domain-optimized rolling strategies affect the depth uniformity at intermediate survey years and present new metrics directly connecting depth uniformity with science return. We characterize the amount of survey area at high risk of being lost in static-science analyses of a rolling LSST data set due to insufficient survey uniformity. At intermediate data releases, nearly half of the survey could be lost for static science, decreasing the dark energy figure of merit by 40%. We describe additional metrics focused on key analysis tasks, such as photometric redshifts and galaxy clustering. Finally, we propose a new strategy that returns the survey to uniformity at key release years, enabling use of the full area and restoring our metrics to the values they would have in a nonrolling cadence—without losing time domain data relative to a rolling survey with the same number of rolling cycles. These new “uniform rolling” strategies have been incorporated into the LSST baseline strategy.

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 preselection. We primarily address the low signal-to-noise ratio (S/N) regime (4.8 ≤ S/N ≤ 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, 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 (S/N > 5.5), and 85.1%, 78.2%, and 84.4% in the low-S/N regime. Using HETDEX LAEs independently identified by Dark Energy Spectroscopic Instrument (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 ∼ 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.