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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. 

Abstract We present a measurement of the Lyαintensity mapping power spectrum from the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX). We measure the cross-power spectrum of the Lyαintensity and Lyα-emitting galaxies (LAEs) in a redshift range of 1.9 ≤z≤ 3.5. We calculate the intensity from HETDEX spectra that do not contain any detected LAEs above a signal-to-noise ratio of 5.5. To produce a power spectrum model and its covariance matrix, we simulate the data using lognormal mocks for the LAE catalog and Lyαintensity in redshift space. The simulations include the HETDEX sensitivity, selection function, and mask. The measurements yield the product of the LAE bias, the intensity bias, the mean intensity of undetected sources, and the ratio of the actual and fiducial redshift-space distortion parameters, $b_{\mathrm{g}}{b}_I〈I〉{\overline{F}}_{\mathrm{RSD}}/{\overline{F}}_{\mathrm{RSD}}^{\mathrm{fid}}=$ (6.7 ± 3.1), (11.7 ± 1.4), and (8.3 ± 1.5) × 10⁻²²erg s⁻¹cm⁻²arcsec⁻²Å⁻¹in three redshift bins centered at $\overline{z}=2.1$ , 2.6, and 3.2, respectively. The results are reasonably consistent with cosmological hydrodynamical simulations that include Lyαradiative transfer. They are, however, significantly smaller than previous results from cross-correlations of quasars with Lyαintensity. These results demonstrate the statistical power of HETDEX for Lyαintensity mapping and pave the way for a more comprehensive analysis. They will also be useful for constraining models of Lyαemission from galaxies used in modern cosmological simulations of galaxy formation and evolution. 

Abstract We used data from the Hobby–Eberly Telescope Dark Energy Experiment (HETDEX) to study the incidence of AGN in continuum-selected galaxies at z ∼ 3. From optical and infrared imaging in the 24 deg 2 Spitzer HETDEX Exploratory Large Area survey, we constructed a sample of photometric-redshift selected z ∼ 3 galaxies. We extracted HETDEX spectra at the position of 716 of these sources and used machine-learning methods to identify those which exhibited AGN-like features. The dimensionality of the spectra was reduced using an autoencoder, and the latent space was visualized through t-distributed stochastic neighbor embedding. Gaussian mixture models were employed to cluster the encoded data and a labeled data set was used to label each cluster as either AGN, stars, high-redshift galaxies, or low-redshift galaxies. Our photometric redshift (photo z ) sample was labeled with an estimated 92% overall accuracy, an AGN accuracy of 83%, and an AGN contamination of 5%. The number of identified AGN was used to measure an AGN fraction for different magnitude bins. The ultraviolet (UV) absolute magnitude where the AGN fraction reaches 50% is M UV = −23.8. When combined with results in the literature, our measurements of AGN fraction imply that the bright end of the galaxy luminosity function exhibits a power law rather than exponential decline, with a relatively shallow faint-end slope for the z ∼ 3 AGN luminosity function. 

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. 

Abstract We have extracted 636 spectra taken at the positions of 583 transient sources from the third data release of the Hobby–Eberly Telescope Dark Energy eXperiment (HETDEX). The transients were discovered by the Zwicky Transient Facility (ZTF) during 2018–2022. The HETDEX spectra provide a potential means to obtain classifications for a large number of objects found by photometric surveys for free. We attempt to explore and classify the spectra by utilizing several template-matching techniques. We have identified two transient sources, ZTF20aatpoos = AT 2020fiz and ZTF19abdkelq, as supernova (SN) candidates. We classify AT 2020fiz as a Type IIP SN observed ∼10 days after explosion, and we propose ZTF19abdkelq as a likely Type Ia SN caught ∼40 days after maximum light. ZTF photometry of these two sources are consistent with their classifications as SNe. Beside these two objects, we have confirmed several ZTF transients as variable active galactic nuclei based on their spectral appearance, and determined the host galaxy types of several other ZTF transients. 

Abstract Supernova (SN) 2023ixf was discovered on 2023 May 19. The host galaxy, M101, was observed by the Hobby–Eberly Telescope Dark Energy Experiment collaboration over the period 2020 April 30–2020 July 10, using the Visible Integral-field Replicable Unit Spectrograph (3470 ≲λ≲ 5540 Å) on the 10 m Hobby–Eberly Telescope. The fiber filling factor within ±30″ of SN 2023ixf is 80% with a spatial resolution of 1″. Ther< 5.″5 surroundings are 100% covered. This allows us to analyze the spatially resolved preexplosion local environments of SN 2023ixf with nebular emission lines. The two-dimensional maps of the extinction and the star formation rate (SFR) surface density (Σ_SFR) show weak increasing trends in the radial distributions within ther< 5.″5 regions, suggesting lower values of extinction and SFR in the vicinity of the progenitor of SN 2023ixf. The median extinction and that of the surface density of SFR withinr< 3″ areE(B−V) = 0.06 ± 0.14, and ${\mathrm{\Sigma }}_{\mathrm{SFR}}={10}^{-5.44\pm 0.66}{M}_{☉}{\mathrm{yr}}^{-1}{\mathrm{arcsec}}^{-2}.$ There is no significant change in extinction before and after the explosion. The gas metallicity does not change significantly with the separation from SN 2023ixf. The metal-rich branch of theR₂₃calculations indicates that the gas metallicity around SN 2023ixf is similar to the solar metallicity (∼Z_☉). The archival deep images from the Canada–France–Hawaii Telescope Legacy Survey (CFHTLS) show a clear detection of the progenitor of SN 2023ixf in thezband at 22.778 ± 0.063 mag, but nondetections in the remaining four bands of CFHTLS (u,g,r,i). The results suggest a massive progenitor of ≈22M_☉. 

Abstract We investigate the stellar mass–black hole mass (  * –  BH ) relation with type 1 active galactic nuclei (AGNs) down to  BH = 10 7 M ⊙ , corresponding to a ≃ −21 absolute magnitude in rest-frame ultraviolet, at z = 2–2.5. Exploiting the deep and large-area spectroscopic survey of the Hobby–Eberly Telescope Dark Energy Experiment (HETDEX), we identify 66 type 1 AGNs with  BH ranging from 10 7 –10 10 M ⊙ that are measured with single-epoch virial method using C iv emission lines detected in the HETDEX spectra.  * of the host galaxies are estimated from optical to near-infrared photometric data taken with Spitzer, the Wide-field Infrared Survey Explorer, and ground-based 4–8 m class telescopes by CIGALE spectral energy distribution (SED) fitting. We further assess the validity of SED fitting in two cases by host-nuclear decomposition performed through surface brightness profile fitting on spatially resolved host galaxies with the James Webb Space Telescope/NIRCam CEERS data. We obtain the  * –  BH relation covering the unexplored low-mass ranges of  BH ∼ 10 7 – 10 8 M ⊙ , and conduct forward modeling to fully account for the selection biases and observational uncertainties. The intrinsic  * –  BH relation at z ∼ 2 has a moderate positive offset of 0.52 ± 0.14 dex from the local relation, suggestive of more efficient black hole growth at higher redshift even in the low-mass regime of  BH ∼ 10 7 – 10 8 M ⊙ . Our  * –  BH relation is inconsistent with the  BH suppression at the low-  * regime predicted by recent hydrodynamic simulations at a 98% confidence level, suggesting that feedback in the low-mass systems may be weaker than those produced in hydrodynamic simulations.