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Abstract We present a deep learning framework to enhance the identification of Lyαemitters (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 acrossz ∼ 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. 

Abstract Gravitational waves (GWs) from compact binary coalescences arestandard sirensthat provide a direct measure of the source’s luminosity distance, enabling an independent measurement of the Hubble constant (H₀). While abright siren—a GW event with an identified electromagnetic (EM) counterpart—provided the first such constraint, most detections, currently dominated by black hole mergers, lack EM signatures. A measurement ofH₀is still possible with thesedark sirensby statistically associating GW events with galaxies in existing catalogs based on the sky localization. In this work, we explore the potential of two subsets of dark sirens categorized by their localization precision: ’golden’ dark sirens, defined by a sky area localization ≤0.1deg², and ’silver’ dark sirens, which are more common but less precisely localized (≤1deg²). Using thefifth internal data releaseof the Hobby–Eberly Telescope Dark Energy Experiment (HETDEX), we assess the suitability of the Visible Integral-field Replicable Unit Spectrograph (VIRUS) for spectroscopic follow-up of dark sirens. VIRUS exposures of the standard HETDEX depth provide precise redshifts and exquisite completeness withinz= 0.2. After a single year of observations with the upgraded LIGO-A^#network, the combined sample of golden and silver dark sirens withz≤ 0.2 atH₀ = 70 km s⁻¹Mpc⁻¹and follow-up VIRUS observations can potentially yield a few-percent constraint onH₀. Our predictions suggest that spectroscopic redshift surveys such as HETDEX can play a key role in realizing high-precision cosmology with dark sirens in the near future. 

Abstract We are merging a large participatory science effort with machine learning to enhance the Hobby–Eberly Telescope Dark Energy Experiment (HETDEX). Our overall goal is to remove false positives, allowing us to use lower signal-to-noise data and sources with low goodness-of-fit. With six million classifications through Dark Energy Explorers, we can confidently determine if a source is not real at over 94% confidence level when classified by at least 10 individuals; this confidence level increases for higher signal-to-noise sources. To date, we have only been able to apply this direct analysis to 190,000 sources. The full sample of HETDEX will contain around 2–3 million sources, including nearby galaxies ([Oii] emitters), distant galaxies (Lyαemitters or LAEs), false positives, and contamination from instrument issues. We can accommodate this tenfold increase by using machine learning with visually vetted samples from Dark Energy Explorers. We have already increased by over tenfold the number of sources that have been visually vetted from our previous pilot study where we only had 14,000 visually vetted LAE candidates. This paper expands on the previous work by increasing the visually vetted sample from 14,000 to 190,000. In addition, using our currently visually vetted sample, we generate a real or false positive classification for the full candidate sample of 1.2 million LAEs. We currently have approximately 17,000 volunteers from 159 countries around the world. Thus, we are applying participatory or citizen scientist analysis to our full HETDEX data set, creating a free educational opportunity that requires no prior technical knowledge. 

The Hobby–Eberly Dark Energy Experiment (HETDEX) is an untargeted ∼540 deg^2 spectroscopic survey of Ly-alpha emission in the 1.9 < z < 3.5 Universe. In surface brightness, this survey reaches 1 sigma Ly-alpha sensitivities of ∼2─5 × 10^−18 erg s−1 cm^−2 arcsec^−2 , allowing large samples of extended Ly-alpha nebulae (LAN) to be studied. We selected a sample of 70,691 Ly-alpha emitting galaxies (LAEs) with an emission-line signal-to-noise ratio greater than 6 and modeled the Ly-alpha emission as a point-source component with an optional exponential envelope. Half (∼47.5%) of the LAE sample (33,612 objects) exhibits significant extended emission and is best fit by the two-component model. The fraction of resolved sources increases with Ly-alpha flux and luminosity. Their isophotal areas range from 10 to 130 arcsec^2 (median 15 arcsec^2), with integrated Ly-alpha luxes from 6 to 2000 × 10^−17 erg s^−1 cm^−2 (median 20 × 10^−17 erg s^−1 cm^−2). Comparison between point-spread function-weighted and isophotal flux measurements shows that the HETDEX pipeline underestimates the total Ly-alpha flux by ∼30% on average, reflecting the substantial halo contribution in extended sources. Approximately 420 LANs are found per deg^2 over 79.5 deg^2 of noncontiguous sky. About 12% of resolved sources show active galactic nuclei signatures and are bright in Ly-alpha and continuum. The remaining 88% span a wide range of morphologies and often lack continuum counterparts. Exponential scale lengths show no strong correlation with Ly-alpha flux or luminosity (median 11.6 ± 1.9 kpc). Only 2.9% of the full S/N > 6 LAE population with ancillary data have radio counterparts, but 64% of those are found to be extended, with the radio fraction increasing with Ly-alpha size. We present a catalog of all modeled sources, with their positions, redshifts, luminosities, and structural parameters for over 70,000 LAEs consisting of 33,000 spatially extended LAN. 

The Hobby–Eberly Telescope Dark Energy Experiment (HETDEX) is a wide-field, integral-field spectroscopic survey designed to map the large-scale distribution of Ly-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 ith ∼1.″8 image quality, enabling an untargeted census of emission-line galaxies across 540 deg^2. We present HETDEX Public Data Release 1 (PDR1), comprising 431,713 IFU observations covering 86.67 deg^2 of noncontiguous sky in the Spring (13h, +51°) and Fall (1 .h 5, 0°) fields, along with legacy regions (Cosmic Evolution Survey, Great Observations Origins Deep Survey North, North Ecliptic Pole, SA22). PDR1 includes the HETDEX Public Source Catalog 2 (HPSC2), an expanded and reprocessed version of E. 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 [OII] 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. 

Abstract We present measurements ofz ∼ 2.4 ultraviolet (UV) background light using Lyαabsorption from galaxies atz ∼ 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 UV light from background galaxies is absorbed by Hiwithin the halo of a foreground galaxy, in a configuration similar to damped Lyαsystems. 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 oversubtracted is representative of thez ∼ 2.4 UV contribution to the overall extragalactic background light (EBL) at Lyα. Using this method, we determine an average intensity (inνJ_νunits) of 12.9 ± 3.7 nW m⁻²sr⁻¹at a median observed wavelength of 4134 Å, or a rest-frame UV background intensity of 508 ± 145 nW m⁻²sr⁻¹atz ∼ 2.4. 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. 

Abstract Investigating the impact of galaxy properties on emergent Lyαemission is crucial for reionization studies, given the sensitivity of Lyαto neutral hydrogen. This study presents an analysis of the physical characteristics of 155 star-forming galaxies, 29 with Lyαdetected, and 126 with Lyαnot detected with LyαEW < 20 Å, atz= 1.9–3.5, drawn from the MOSFIRE Deep Evolution Field survey, that have overlapping observations from the Hobby–Eberly Telescope Dark Energy Experiment survey. To unravel the interstellar medium (ISM) conditions in our sample, we developed a custom nebular line modeling algorithm based on the MAPPINGS V photoionization model grid and theemceeframework. Combining nebular-based ISM properties with photometry-based global properties, constrained viaBagpipes, we explore distinctions in the stellar and gas properties between Lyα-detected and Lyα-nondetected galaxies. Our analysis reveals statistically significant differences between the two samples in terms of stellar mass and dust attenuation (A_V) at >2σsignificance, as determined via a Kolmogorov–Smirnov test. Moreover, there are weaker (≲1σsignificance) indications that the ionization parameter and metallicity differ between the two samples. Our results demonstrate that the escape fraction of Lyα( $f_{\mathrm{esc}}^{\mathrm{Ly}\alpha }$ ) is inversely correlated with stellar mass, star formation rate, and dust attenuation, while it is positively correlated with the ionization parameter, with significance levels exceeding 2σ. Our findings suggest that the interstellar environments of Lyα-detected galaxies, characterized by low mass, low dust, low gas-phase metallicity, and high ionization parameters, play a pivotal role in promoting the escape of Lyαradiation. 

Abstract We present cosmological-scale three-dimensional neutral hydrogen (Hi) tomographic maps atz= 2–3 over a total of 837 deg²in two blank fields that are developed with Lyαforest absorptions of 14,736 background Sloan Digital Sky Survey (SDSS) quasars atz= 2.08–3.67. Using the tomographic maps, we investigate the large-scale (≳10h⁻¹cMpc) average Hiradial profiles and two-direction profiles of the line-of-sight (LOS) and transverse directions around galaxies and active galactic nuclei (AGNs) atz= 2–3 identified by the Hobby–Eberly Telescope Dark Energy eXperiment survey and SDSS, respectively. The peak of the Hiradial profile around galaxies is lower than the one around AGNs, suggesting that the dark matter halos of galaxies are less massive on average than those of AGNs. The LOS profile of AGNs is narrower than the transverse profile, indicating the Kaiser effect. There exist weak absorption outskirts at ≳30h⁻¹cMpc beyond Histructures of galaxies and AGNs found in the LOS profiles that can be explained by the Higas at ≳30h⁻¹cMpc falling toward the source position. Our findings indicate that the Hiradial profile of AGNs has transitions from proximity zones (≲a fewh⁻¹cMpc) to the Histructures (∼1–30h⁻¹cMpc) and the weak absorption outskirts (≳30h⁻¹cMpc). Although there is no significant dependence of AGN types (type 1 vs. type 2) on the Hiprofiles, the peaks of the radial profiles anticorrelate with AGN luminosities, suggesting that AGNs’ ionization effects are stronger than the gas mass differences. 

Abstract We present analysis using a citizen science campaign to improve the cosmological measures from the Hobby–Eberly Telescope Dark Energy Experiment (HETDEX). The goal of HETDEX is to measure the Hubble expansion rate, H ( z ), and angular diameter distance, D A ( z ), at z = 2.4, each to percent-level accuracy. This accuracy is determined primarily from the total number of detected Ly α emitters (LAEs), the false positive rate due to noise, and the contamination due to [O ii ] emitting galaxies. This paper presents the citizen science project, Dark Energy Explorers ( https://www.zooniverse.org/projects/erinmc/dark-energy-explorers ), with the goal of increasing the number of LAEs and decreasing the number of false positives due to noise and the [O ii ] galaxies. Initial analysis shows that citizen science is an efficient and effective tool for classification most accurately done by the human eye, especially in combination with unsupervised machine learning. Three aspects from the citizen science campaign that have the most impact are (1) identifying individual problems with detections, (2) providing a clean sample with 100% visual identification above a signal-to-noise cut, and (3) providing labels for machine-learning efforts. Since the end of 2022, Dark Energy Explorers has collected over three and a half million classifications by 11,000 volunteers in over 85 different countries around the world. By incorporating the results of the Dark Energy Explorers, we expect to improve the accuracy on the D A ( z ) and H ( z ) parameters at z = 2.″4 by 10%–30%. While the primary goal is to improve on HETDEX, Dark Energy Explorers has already proven to be a uniquely powerful tool for science advancement and increasing accessibility to science worldwide.