arXiv subjects

Lindsay R. House

Publications and source records attributed to Lindsay R. House.

13 recordsLinked to original sources

arXiv2026

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).

astro-ph.GA↗

arXiv2026

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.

astro-ph.GA↗

arXiv2026

Opportunities in AI/ML for the Rubin LSST Dark Energy Science Collaboration

The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will produce unprecedented volumes of heterogeneous astronomical data (images, catalogs, and alerts) that challenge traditional analysis pipelines. The LSST Dark Energy Science Collaboration (DESC) aims to derive robust constraints on dark energy and dark matter from these data, requiring methods that are statistically powerful, scalable, and operationally reliable. Artificial intelligence and machine learning (AI/ML) are already embedded across DESC science workflows, from photometric redshifts and transient classification to weak lensing inference and cosmological simulations. Yet their utility for precision cosmology hinges on trustworthy uncertainty quantification, robustness to covariate shift and model misspecification, and reproducible integration within scientific pipelines. This white paper surveys the current landscape of AI/ML across DESC's primary cosmological probes and cross-cutting analyses, revealing that the same core methodologies and fundamental challenges recur across disparate science cases. Since progress on these cross-cutting challenges would benefit multiple probes simultaneously, we identify key methodological research priorities, including Bayesian inference at scale, physics-informed methods, validation frameworks, and active learning for discovery. With an eye on emerging techniques, we also explore the potential of the latest foundation model methodologies and LLM-driven agentic AI systems to reshape DESC workflows, provided their deployment is coupled with rigorous evaluation and governance. Finally, we discuss critical software, computing, data infrastructure, and human capital requirements for the successful deployment of these new methodologies, and consider associated risks and opportunities for broader coordination with external actors.

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arXiv2025

Picture an Astronomer: Best Practices for Retaining Talent in Astrophysics

Women are consistently underrepresented in astrophysics yet are simultaneously subject to disproportionate attrition at every career stage. This disparity between demonstrated efficacy in job performance and ultimate career outcome was the primary motivation for the Picture an Astronomer series, which included both targeted public outreach to increase representation of women in astrophysics and high-level, solution-oriented discussions among professional astronomers. In March 2025, more than 200 astronomers came together in a hybrid-format symposium focused on the state of the field for female scientists, combining scientific exchange with discussions of policies and practices to strengthen retention of talent in the field. This white paper is the result of those discussions, offering a wide range of recommendations developed in the context of gendered attrition in astrophysics but which ultimately support a healthier climate for all scientists alike.

astro-ph.IM↗

arXiv2025

A JWST MIRI LRS Survey of 37 Massive Star-Forming Galaxies and AGN at Cosmic Noon -- Overview and First Results

We present a large spectroscopic survey with \textit{JWST}'s Mid-Infrared Instrument (MIRI) Low Resolution Spectrometer (LRS) targeting $37$ infrared-bright galaxies between $z=0.65-2.46$ with infrared luminosities $\log L_{\rm IR}/L_\odot>11.5$ and $\log M_*/M_\odot=10-11.5$. Targets were taken from a \textit{Spitzer} $24\,μ$m-selected sample with archival spectroscopy from the Infrared Spectrograph (IRS) and include a mix of star-forming galaxies and dust-obscured AGN. By combining IRS with the increased sensitivity of LRS, we expand the range of spectral features observed between $5-30\,μ$m for every galaxy in our sample. In this paper, we outline the sample selection, \textit{JWST} data reduction, 1D spectral extraction, and polycyclic aromatic hydrocarbon (PAH) feature measurements from $λ_{rest}=3.3-11.2\,μ$m. In the \textit{JWST} spectra, we detect PAH emission features at $3.3-5.3\,μ$m, as well as Paschen and Brackett lines. The $3.3\,μ$m feature can be as bright as $1\%$ of the $8-1000\,μ$m infrared luminosity and exhibits a tight correlation with the dust-obscured star-formation rate. We detect absorption features from CO gas, CO$_2$ ice, H$_2$O ice, and aliphatic dust. From the joint \textit{JWST} and \textit{Spitzer} analysis we find that the $11.3/3.3\,μ$m PAH ratios are on-average three times higher than that of local luminous, infrared galaxies. This is interpreted as evidence that the PAH grains are larger at $z\sim1-2$. The size distribution may be affected by coagulation of grains due to high gas densities and low temperatures. These conditions are supported by the observation of strong water ice absorption at $3.05\,μ$m, and can lower stellar radiative feedback as large PAHs transmit less energy per photon into the interstellar medium.

astro-ph.GA↗

arXiv2025

Informal Education is Essential to Physics: Findings of the 2024 JNIPER Summit and Recommendations for Action

In order to reach the full civic and scientific potential of physics, this white paper calls for a culture change in physics to recognize informal physics education (also referred to as public engagement or outreach) as an essential disciplinary practice. That is, engaging in informal physics education (IPE) is part of what it means to ''do physics.'' In June 2024, we hosted a summit with forty-two members of the Joint Network for Informal Physics Education and Research (JNIPER) to discuss concrete steps for fostering this cultural shift in physics. We present key findings from the Summit to motivate this culture change: IPE makes the work of physicists relevant; fosters trust and supports a society where everyone benefits from science and technology advances; serves as a gateway for entering into the physics discipline, and for staying once there; and improves physicists' skills and research. We identify three levers for promoting the culture change: structures supporting IPE; engagement of interested, influential, and/or impacted parties; and integration of research-based IPE practices. Each lever is accompanied by associated recommendations for action directed at individuals, departments and institutions, topical groups such as JNIPER, and funders and (inter)national organizations. Our clarion call is for members and supporters of the IPE community to choose one recommendation per lever to prioritize and to set forth a roadmap for implementation. Together, we can establish IPE as a central physics practice, ultimately leading to a deeper connection between physics and society, strengthening our mutual potential and impact for good.

physics.ed-ph↗

arXiv2024

Participatory Science and Machine Learning Applied to Millions of Sources in the Hobby-Eberly Telescope Dark Energy Experiment

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 ten 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 2-3M sources, including nearby galaxies ([O II] emitters), distant galaxies (Lyman-alpha emitters 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 ten-fold in 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 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 dataset, creating a free educational opportunity that requires no prior technical knowledge.

astro-ph.IM↗

arXiv2024

Absorption Troughs of Lyman Alpha Emitters in HETDEX

The Hobby-Eberly Telescope Dark Energy Experiment (HETDEX) is designed to detect and measure the redshifts of more than one million Ly$α$ emitting galaxies (LAEs) between $1.88 < z < 3.52$. In addition to its cosmological measurements, these data enable studies of Ly$α$ spectral profiles and the underlying radiative transfer. Using the roughly half a million LAEs in the HETDEX Data Release 3, we stack various subsets to obtain the typical Ly$α$ profile for the $z \sim 2-3$ epoch and to understand their physical properties. We find clear absorption wings around Ly$α$ emission, which extend $\sim 2000$ km $\mathrm{s}^{-1}$ both redward and blueward of the central line. Using far-UV spectra of nearby ($0.002 < z < 0.182$) LAEs in the CLASSY treasury and optical/near-IR spectra of $2.8 < z < 6.7$ LAEs in the MUSE-Wide survey, we observe absorption profiles in both redshift regimes. Dividing the sample by volume density shows that the troughs increase in higher density regions. This trend suggests that the depth of the absorption is dependent on the local density of objects near the LAE, a geometry that is similar to damped Lyman-$α$ systems. Simple simulations of Ly$α$ radiative transfer can produce similar troughs due to absorption of light from background sources by HI gas surrounding the LAEs.

astro-ph.GA↗

arXiv2023

HETDEX Public Source Catalog 1 -- Stacking 50K Lyman Alpha Emitters

We describe the ensemble properties of the $1.9 < z < 3.5$ Lyman Alpha Emitters (LAEs) found in the HETDEX survey's first public data release, HETDEX Public Source Catalog 1 (Mentuch Cooper et al. 2023). Stacking the low-resolution ($R \sim$ 800) spectra greatly increases the signal-to-noise ratio, revealing spectral features otherwise hidden by noise, and we show that the stacked spectrum is representative of an average member of the set. The flux limited, Ly$α$ signal-to-noise ratio restricted stack of 50K HETDEX LAEs shows the ensemble biweight ``average" $z \sim 2.6$ LAE to be a blue (UV continuum slope $\sim -2.4$ and E(B-V) $< 0.1$), moderately bright (M$_{\text{UV}} \sim -19.7$) star forming galaxy with strong Ly$α$ emission (log $L_{Lyα}$ $\sim$ 42.8 and $W_λ$(Ly$α$) $\sim$ 114Å), and potentially significant leakage of ionizing radiation. The restframe UV light is dominated by a young, metal poor stellar population with an average age 5-15 Myr and metallicity of 0.2-0.3 Z$_{\odot}$.

astro-ph.GA↗

arXiv2023

Using Dark Energy Explorers and Machine Learning to Enhance the Hobby-Eberly Telescope Dark Energy Experiment

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 Lyman-$α$ 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, with the goal of increasing the number of LAEs, 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.

astro-ph.IM↗

arXiv2023

HETDEX Public Source Catalog 1: 220K Sources Including Over 50K Lyman Alpha Emitters from an Untargeted Wide-area Spectroscopic Survey

We present the first publicly released catalog of sources obtained from the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX). HETDEX is an integral field spectroscopic survey designed to measure the Hubble expansion parameter and angular diameter distance at 1.88<z<3.52 by using the spatial distribution of more than a million Ly-alpha-emitting galaxies over a total target area of 540 deg^2. The catalog comes from contiguous fiber spectra coverage of 25 deg^2 of sky from January 2017 through June 2020, where object detection is performed through two complementary detection methods: one designed to search for line emission and the other a search for continuum emission. The HETDEX public release catalog is dominated by emission-line galaxies and includes 51,863 Lyα-emitting galaxy (LAE) identifications and 123,891 OII-emitting galaxies at z<0.5. Also included in the catalog are 37,916 stars, 5274 low-redshift (z<0.5) galaxies without emission lines, and 4976 active galactic nuclei. The catalog provides sky coordinates, redshifts, line identifications, classification information, line fluxes, OII and Ly-alpha line luminosities where applicable, and spectra for all identified sources processed by the HETDEX detection pipeline. Extensive testing demonstrates that HETDEX redshifts agree to within deltaz < 0.02, 96.1% of the time to those in external spectroscopic catalogs. We measure the photometric counterpart fraction in deep ancillary Hyper Suprime-Cam imaging and find that only 55.5% of the LAE sample has an r-band continuum counterpart down to a limiting magnitude of r~26.2 mag (AB) indicating that an LAE search of similar sensitivity with photometric pre-selection would miss nearly half of the HETDEX LAE catalog sample. Data access and details about the catalog can be found online at http://hetdex.org/.

astro-ph.GA↗

arXiv2023

The HETDEX Survey: Emission Line Exploration and Source Classification

The Hobby-Eberly Telescope Dark Energy Experiment (HETDEX) is an untargeted spectroscopic survey that aims to measure the expansion rate of the Universe at $z \sim 2.4$ to 1% precision for both $H(z)$ and $D_A(z)$. HETDEX is in the process of mapping in excess of one million Lyman Alpha emitting (LAE) galaxies and a similar number of lower-z galaxies as a tracer of the large-scale structure. The success of the measurement is predicated on the post-observation separation of galaxies with Ly$α$ emission from the lower-$z$ interloping galaxies, primarily [OII], with low contamination and high recovery rates. The Emission Line eXplorer (ELiXer) is the principal classification tool for HETDEX, providing a tunable balance between contamination and completeness as dictated by science needs. By combining multiple selection criteria, ELiXer improves upon the 20 Angstrom rest-frame equivalent width cut commonly used to distinguish LAEs from lower-$z$ [OII] emitting galaxies. Despite a spectral resolving power, R $\sim800$, that cannot resolve the [OII] doublet, we demonstrate the ability to distinguish LAEs from foreground galaxies with 98.1% accuracy. We estimate a contamination rate of Ly$α$ by [OII] of 1.2% and a Ly$α$ recovery rate of 99.1% using the default ELiXer configuration. These rates meet the HETDEX science requirements.

astro-ph.GA↗

arXiv2021

The Hobby-Eberly Telescope Dark Energy Experiment (HETDEX) Survey Design, Reductions, and Detections

We describe the survey design, calibration, commissioning, and emission-line detection algorithms for the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX). The goal of HETDEX is to measure the redshifts of over a million Ly$α$ emitting galaxies between 1.88<z<3.52, in a 540 deg^2 area encompassing a co-moving volume of 10.9 Gpc^3. No pre-selection of targets is involved; instead the HETDEX measurements are accomplished via a spectroscopic survey using a suite of wide-field integral field units distributed over the focal plane of the telescope. This survey measures the Hubble expansion parameter and angular diameter distance, with a final expected accuracy of better than 1%. We detail the project's observational strategy, reduction pipeline, source detection, and catalog generation, and present initial results for science verification in the COSMOS, Extended Groth Strip, and GOODS-N fields. We demonstrate that our data reach the required specifications in throughput, astrometric accuracy, flux limit, and object detection, with the end products being a catalog of emission-line sources, their object classifications, and flux-calibrated spectra.

astro-ph.IM↗