arXiv subjects

J. E. G. Peek

Publications and source records attributed to J. E. G. Peek.

At least 19 recordsLinked to original sources

arXiv2026

LightCube: A Parsec-Resolution 3D Model of the Local Far-Ultraviolet Interstellar Radiation Field

We present a three-dimensional model of the local interstellar radiation field (ISRF) in the ultraviolet (UV). Using UV flux measurements from the TD1 catalog and stellar distances from Gaia and Hipparcos, we construct a catalog of stars that we expect to dominate the UV flux in the nearby Galaxy. We use the radiative transfer code DIRTY to model the propagation of photons from these stars through a 3D dust map, including the effects of scattering and absorption. The result is LightCube, a model of the ultraviolet ISRF out to 1.25 kpc from the Sun, with a maximum linear resolution of 1 pc. We model the ISRF in the four TD1 bands (1565 A, 1965 A, 2365 A, and 2740 A), as well as a single value for the full FUV range, and calculate the ISRF at the Sun to be 5.65$\times$10$^{-14}$ erg cm$^{-3}$ from 912 A to 2000 A. The modeled ISRF is quite variable, with more than an order of magnitude variation seen in dense regions, and about half that in lower density regions. By comparing LightCube to an estimate of the 3D distribution of total-to-selective extinction ratio, $R_V$, we find a positive correlation between UV flux and $R_V$ in regions of low UV radiation.

astro-ph.GA↗

arXiv2025

The Impact of the MAST Data Archive

The Barbara A. Mikulski Archive for Space Telescopes (MAST) hosts science-ready data products from over twenty NASA missions, plus community-contributed data collections, and other select surveys. The data support forefront research in the ultraviolet, optical, and near-infrared wavelength bands. We have constructed bibliographies for each mission from publications in nearly 40 professional journals, and have identified more than 37,000 refereed articles where investigators made a science usage of data hosted in MAST. The publication rate over the last 50 years shows that most MAST missions have had very high productivity during their in-service lifetimes, and have remained so for years or decades afterward. Annual citations to these publications, a measure of impact on research, are robust for most missions, with citations that grow over more than a decade. Most of the citations come from about 10% of articles within each mission. We examined the bibliographies of the active missions HST and JWST in greater detail. For HST the rate of archival publications exceeded those authored by the original observing teams within a decade of launch, and is now more than 3 times higher. Early indications hint that JWST archival articles could dominate the publication rate even sooner. The production of articles resulting from any given observing program can extend for decades. Programs with small and very large allocations of observing time tend to be particularly productive per unit of observing time. For HST in general, a first publication appears within 1.5 yr for 50% of observing programs, and within 3.8 yr for 80% of programs. We discuss various external factors that affect publication metrics, their strengths and limitations for measuring scientific impact, and the challenges of making meaningful comparisons of publication metrics across missions.

astro-ph.IM↗

arXiv2025

A Catalog of Galactic Atomic Hydrogen Position-Position-Velocity Filaments

We present a catalog of 3D Galactic HI filaments over 1/3 of the sky using Galactic Arecibo L-band Feed Array HI (GALFA-HI) data. The 3D filaments are defined to be linear HI features that are continuous in position-position-velocity (PPV) and are found with fil3d, an algorithm that expands on the 2D FilFinder. The catalog contains 3333 HI filaments between +/- 50 km/s at a range of Galactic positions. 1542 of the PPV filaments are identified as local at the distance of the wall of the Local Bubble, and 209 are likely at the disk-halo interface of our Galaxy. The catalog and properties of the PPV filaments are obtained after an unsharp mask (USM) is applied to the data. The widths of the filaments are consistently ~12' (0.34 pc at 100 pc), and constrained by the 4' resolution. The local filaments have median properties of N_HI = $6 \times 10^{18}$ cm$^{-2}$, M_HI = 0.17 M_sun, FWHM = 3.2 km/s, and length of 6.4 pc. The disk-halo population has similar column densities, but the median FWHM = 7.7 km/s, consistent with them being higher z-height, warmer structures. The L $\propto$ M$^{0.5}$ relationship found for the HI filaments and their bundling on the sky are consistent with a hierarchical structure, and is likely related to turbulence playing a role in their formation.

astro-ph.GA↗

arXiv2025

The Plane Quasar Survey: An Ionized Extension of the Magellanic Stream on the Northern Side of the Galactic Plane

The Magellanic Stream (MS) is a vast gaseous structure in the Milky Way halo, containing most of its mass in ionized form and tracing the interaction between the Large and Small Magellanic Clouds and the Galaxy. Using HST/COS G160M spectra from the Plane Quasar Survey, we detect C IV absorbers likely associated with the MS, extending to the northern side of the Galactic plane, approximately 60$^\circ$ beyond its previously known ionized extent. These absorbers exhibit position and kinematic alignment and show consistent ionization trends with previously studied MS sight lines. The non-detection of low ions such as Al II and Si II, and the detection of C IV (and Si IV in some sightlines), indicates a highly ionized gas phase. The observed Si IV/C IV column density ratios suggest a gas temperature of $T \sim 10^{5.3}$~K and favor collisional ionization over photoionization. We estimate the newly detected extension increases the previous ionized gas mass of the MS, and its coherent kinematics suggest that it was stripped within the past few hundred Myr and has not yet mixed with the Milky Way halo. The existence of highly-ionized MS gas at a location above the Galactic Plane may constrain the orbital direction of the Magellanic Clouds.

astro-ph.GA↗

arXiv2025

From Queries to Criteria: Understanding How Astronomers Evaluate LLMs

There is growing interest in leveraging LLMs to aid in astronomy and other scientific research, but benchmarks for LLM evaluation in general have not kept pace with the increasingly diverse ways that real people evaluate and use these models. In this study, we seek to improve evaluation procedures by building an understanding of how users evaluate LLMs. We focus on a particular use case: an LLM-powered retrieval-augmented generation bot for engaging with astronomical literature, which we deployed via Slack. Our inductive coding of 368 queries to the bot over four weeks and our follow-up interviews with 11 astronomers reveal how humans evaluated this system, including the types of questions asked and the criteria for judging responses. We synthesize our findings into concrete recommendations for building better benchmarks, which we then employ in constructing a sample benchmark for evaluating LLMs for astronomy. Overall, our work offers ways to improve LLM evaluation and ultimately usability, particularly for use in scientific research.

cs.CL↗

arXiv2025

A Nearby Dark Molecular Cloud in the Local Bubble Revealed via H$_2$ Fluorescence

A longstanding prediction in interstellar theory posits that significant quantities of molecular gas, crucial for star formation, may be undetected due to being ``dark" in commonly used molecular gas tracers, such as carbon monoxide. We report the discovery of Eos, the closest dark molecular cloud, located just 94 parsecs from the Sun. This cloud is the first molecular cloud ever to be identified using H$_2$ far ultra-violet (FUV) fluorescent line emission, which traces molecular gas at the boundary layers of star-forming and supernova remnant regions. The cloud edge is outlined along the high-latitude side of the North Polar Spur, a prominent x-ray/radio structure. Our distance estimate utilizes 3D dust maps, the absorption of the soft X-ray background, and hot gas tracers such as O\,{\sc vi}; these place the cloud at a distance consistent with the Local Bubble's surface. Using high-latitude CO maps we note a small amount (M$_{\rm{H}_2}\approx$20-40\,M$_\odot$) of CO-bright cold molecular gas, in contrast with the much larger estimate of the cloud's true molecular mass (M$_{\rm{H}_2}\approx3.4\times 10^3$\,M$_\odot$), indicating most of the cloud is CO-dark. Combining observational data with novel analytical models and simulations, we predict this cloud will photoevaporate in 5.7 million years, placing key constraints on the role of stellar feedback in shaping the closest star-forming regions to the Sun.

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arXiv2025

The Hubble Image Similarity Project

We have created a large database of similarity information between sub-regions of Hubble Space Telescope images. These data can be used to assess the accuracy of image search algorithms based on computer vision methods. The images were compared by humans in a citizen science project, where they were asked to select similar images from a comparison sample. We utilized the Amazon Mechanical Turk system to pay our reviewers a fair wage for their work. Nearly 850,000 comparison measurements have been analyzed to construct a similarity distance matrix between all the pairs of images. We describe the algorithm used to extract a robust distance matrix from the (sometimes noisy) user reviews. The results are very impressive: the data capture similarity between images based on morphology, texture, and other details that are sometimes difficult even to describe in words (e.g., dusty absorption bands with sharp edges). The collective visual wisdom of our citizen scientists matches the accuracy of the trained eye, with even subtle differences among images faithfully reflected in the distances.

astro-ph.IM↗

arXiv2025

Origin of the IRAS Vela Shell: New Insights from 3D Dust Mapping

The IRAS Vela Shell (IVS) is a structure of enhanced FIR emission located towards the Gum Nebula, a prominent region of $\rm Hα$ emission in the local Milky Way shaped by various galactic stellar feedback over the past several million years. We constrain the 3D spatial geometry of the IVS using a parsec-resolution 3D dust map and contextualize it within the broader Gum Nebula. Our analysis reveals a dense, bowl-like IVS structure below the Galactic plane, with a more diffuse component above. We obtain a total shell mass of $5.1_{-2.4}^{+2.4}\times 10^{4}\;\rm M_{\odot}$ and, incorporating previous studies on shell expansion, a momentum of $6.0_{-3.4}^{+4.7}\times 10^{5}\;\rm M_{\odot}\;km\; s^{-1}$. We find a spatial correlation between the morphology of the dust-traced IVS and the Gum Nebula's $\rm Hα$ emission when projected onto the sky. We quantify contributions of feedback from stellar winds, an expanding HII region, and supernovae to the IVS formation, finding that stellar winds are subdominant. Our momentum analysis shows that both an HII region and supernova feedback could drive the shell's expansion. Using astrometric constraints from Gaia and Hipparcos, we trace back nearby feedback sources and find that the massive stars $\gamma2$ Velorum and $ζ$ Puppis are currently within the IVS, producing enough ionizing luminosity to form an HII region of comparable size. Alternatively, if the IVS' momentum is primarily driven by supernovae, $1-2$ events would be required. We also identify several young massive clusters that could have hosted supernovae within the past 3 Myr.

astro-ph.GA↗

arXiv2025

Kinetic tomography of the Galactic plane within 1.25 kiloparsecs from the Sun. The interstellar flows revealed by HI and CO line emission and 3D dust

We present a reconstruction of the line-of-sight motions of the local interstellar medium (ISM) based on the combination of a model of the three-dimensional dust density distribution within 1.25 kpc from the Sun and the HI and CO line emission within Galactic latitudes $|b| < 5^{\circ}$. We used the histogram of oriented gradient (HOG) method, a computer vision technique for evaluating the morphological correlation between images, to match the plane-of-the-sky dust distribution across distances with the atomic and molecular line emission. We identified a significant correlation between the 3D dust model and the line emission. We employed this correlation to assign line-of-sight velocities to the dust across density channels and produce a face-on map of the local ISM radial motions with respect to the local standard of rest (LSR). We find that most of the material in the 3D dust model follows the large-scale pattern of Galactic rotation; however, we also report local departures from the rotation pattern with standard deviations of 10.8 and 6.6 km/s for the HI and CO line emission, respectively. The mean kinetic energy densities corresponding to these streaming motions are around 0.11 and 0.04 eV/cm$^{3}$ from either gas tracer. Assuming homogeneity and isotropy in the velocity field, these values are within a factor of a few of the total kinetic energy density. These kinetic energy values are roughly comparable to other energy densities, thus confirming the near-equipartition in the local ISM. Yet, we identify energy and momentum overdensities of around a factor of ten concentrated in local density structures. Although we do not find evidence of the local spiral arm's impact on these energy overdensities, their distribution suggests the influence of large-scale effects that, in addition to supernova feedback, shape the energy distribution and dynamics in the solar neighborhood.

astro-ph.GA↗

arXiv2024

Scylla I: A pure-parallel, multi-wavelength imaging survey of the ULLYSES fields in the LMC and SMC

Scylla is a deep Hubble Space Telescope survey of the stellar populations, interstellar medium and star formation in the LMC and SMC. As a pure-parallel complement to the Ultraviolet Legacy Library of Young Stars as Essential Standards (ULLYSES) survey, Scylla obtained 342 orbits of ultraviolet (UV) through near-infrared (IR) imaging of the LMC and SMC with Wide Field Camera 3. In this paper, we describe the science objectives, observing strategy, data reduction procedure, and initial results from our photometric analysis of 96 observed fields. Although our observations were constrained by ULYSSES primary exposures, we imaged all fields in at least two filters (F475W and F814W), and 64% of fields in at least three and as many as seven WFC3 filters spanning the UV to IR. Overall, we reach average 50% completeness of $m_{\rm F225W}=26.0$, $m_{\rm F275W}=26.2$, $m_{\rm F336W}=26.9$, $m_{\rm F475W}=27.8$, $m_{\rm F814W}=25.5$, $m_{\rm F110W}=24.7$, and $m_{\rm F160W}=24.0$ Vega magnitudes in our photometric catalogs, which is faintward of the ancient main sequence turnoff in all filters. The primary science goals of Scylla include characterizing the structure and properties of dust in the MCs, as well as their spatially-resolved star formation and chemical enrichment histories. Our images and photometric catalogs, which represent the widest-area coverage of MCs with HST photometry to date, are available as a high-level science product at the Barbara A. Mikulski Archive for Space Telescopes.

astro-ph.GA↗

arXiv2024

pathfinder: A Semantic Framework for Literature Review and Knowledge Discovery in Astronomy

The exponential growth of astronomical literature poses significant challenges for researchers navigating and synthesizing general insights or even domain-specific knowledge. We present Pathfinder, a machine learning framework designed to enable literature review and knowledge discovery in astronomy, focusing on semantic searching with natural language instead of syntactic searches with keywords. Utilizing state-of-the-art large language models (LLMs) and a corpus of 350,000 peer-reviewed papers from the Astrophysics Data System (ADS), Pathfinder offers an innovative approach to scientific inquiry and literature exploration. Our framework couples advanced retrieval techniques with LLM-based synthesis to search astronomical literature by semantic context as a complement to currently existing methods that use keywords or citation graphs. It addresses complexities of jargon, named entities, and temporal aspects through time-based and citation-based weighting schemes. We demonstrate the tool's versatility through case studies, showcasing its application in various research scenarios. The system's performance is evaluated using custom benchmarks, including single-paper and multi-paper tasks. Beyond literature review, Pathfinder offers unique capabilities for reformatting answers in ways that are accessible to various audiences (e.g. in a different language or as simplified text), visualizing research landscapes, and tracking the impact of observatories and methodologies. This tool represents a significant advancement in applying AI to astronomical research, aiding researchers at all career stages in navigating modern astronomy literature.

astro-ph.IM↗

arXiv2024

PHANGS-ML: dissecting multiphase gas and dust in nearby galaxies using machine learning

The PHANGS survey uses ALMA, HST, VLT, and JWST to obtain an unprecedented high-resolution view of nearby galaxies, covering millions of spatially independent regions. The high dimensionality of such a diverse multi-wavelength dataset makes it challenging to identify new trends, particularly when they connect observables from different wavelengths. Here we use unsupervised machine learning algorithms to mine this information-rich dataset to identify novel patterns. We focus on three of the PHANGS-JWST galaxies, for which we extract properties pertaining to their stellar populations; warm ionized and cold molecular gas; and Polycyclic Aromatic Hydrocarbons (PAHs), as measured over 150 pc-scale regions. We show that we can divide the regions into groups with distinct multiphase gas and PAH properties. In the process, we identify previously-unknown galaxy-wide correlations between PAH band and optical line ratios and use our identified groups to interpret them. The correlations we measure can be naturally explained in a scenario where the PAHs and the ionized gas are exposed to different parts of the same radiation field that varies spatially across the galaxies. This scenario has several implications for nearby galaxies: (i) The uniform PAH ionized fraction on 150 pc scales suggests significant self-regulation in the ISM, (ii) the PAH 11.3/7.7 \mic~ band ratio may be used to constrain the shape of the non-ionizing far-ultraviolet to optical part of the radiation field, and (iii) the varying radiation field affects line ratios that are commonly used as PAH size diagnostics. Neglecting this effect leads to incorrect or biased PAH sizes.

astro-ph.GA↗

arXiv2023

Constructing Impactful Machine Learning Research for Astronomy: Best Practices for Researchers and Reviewers

Machine learning has rapidly become a tool of choice for the astronomical community. It is being applied across a wide range of wavelengths and problems, from the classification of transients to neural network emulators of cosmological simulations, and is shifting paradigms about how we generate and report scientific results. At the same time, this class of method comes with its own set of best practices, challenges, and drawbacks, which, at present, are often reported on incompletely in the astrophysical literature. With this paper, we aim to provide a primer to the astronomical community, including authors, reviewers, and editors, on how to implement machine learning models and report their results in a way that ensures the accuracy of the results, reproducibility of the findings, and usefulness of the method.

astro-ph.IM↗

arXiv2023

Measuring the 8621 Å Diffuse Interstellar Band in Gaia DR3 RVS Spectra: Obtaining a Clean Catalog by Marginalizing over Stellar Types

Diffuse interstellar bands (DIBs) are broad absorption features associated with interstellar dust and can serve as chemical and kinematic tracers. Conventional measurements of DIBs in stellar spectra are complicated by residuals between observations and best-fit stellar models. To overcome this, we simultaneously model the spectrum as a combination of stellar, dust, and residual components, with full posteriors on the joint distribution of the components. This decomposition is obtained by modeling each component as a draw from a high-dimensional Gaussian distribution in the data-space (the observed spectrum) -- a method we call "Marginalized Analytic Data-space Gaussian Inference for Component Separation" (MADGICS). We use a data-driven prior for the stellar component, which avoids missing stellar features not well-modeled by synthetic spectra. This technique provides statistically rigorous uncertainties and detection thresholds, which are required to work in the low signal-to-noise regime that is commonplace for dusty lines of sight. We reprocess all public Gaia DR3 RVS spectra and present an improved 8621 Å DIB catalog, free of detectable stellar line contamination. We constrain the rest-frame wavelength to $8623.14 \pm 0.087$ Å (vacuum), find no significant evidence for DIBs in the Local Bubble from the $1/6^{\rm{th}}$ of RVS spectra that are public, and show unprecedented correlation with kinematic substructure in Galactic CO maps. We validate the catalog, its reported uncertainties, and biases using synthetic injection tests. We believe MADGICS provides a viable path forward for large-scale spectral line measurements in the presence of complex spectral contamination.

astro-ph.GA↗

arXiv2023

Target Selection and Sample Characterization for the DESI LOW-Z Secondary Target Program

We introduce the DESI LOW-Z Secondary Target Survey, which combines the wide-area capabilities of the Dark Energy Spectroscopic Instrument (DESI) with an efficient, low-redshift target selection method. Our selection consists of a set of color and surface brightness cuts, combined with modern machine learning methods, to target low-redshift dwarf galaxies ($z$ < 0.03) between $19 < r < 21$ with high completeness. We employ a convolutional neural network (CNN) to select high-priority targets. The LOW-Z survey has already obtained over 22,000 redshifts of dwarf galaxies (M$_* < 10^9$ M$_\odot$), comparable to the number of dwarf galaxies discovered in SDSS-DR8 and GAMA. As a spare fiber survey, LOW-Z currently receives fiber allocation for just ~50% of its targets. However, we estimate that our selection is highly complete: for galaxies at $z < 0.03$ within our magnitude limits, we achieve better than 95% completeness with ~1% efficiency using catalog-level photometric cuts. We also demonstrate that our CNN selections $z<0.03$ galaxies from the photometric cuts subsample at least ten times more efficiently while maintaining high completeness. The full five-year DESI program will expand the LOW-Z sample, densely mapping the low-redshift Universe, providing an unprecedented sample of dwarf galaxies, and providing critical information about how to pursue effective and efficient low-redshift surveys.

astro-ph.GA↗

arXiv2023

A panoptic view of the Taurus molecular cloud I. The cloud dynamics revealed by gas emission and 3D dust

We present a study of the three-dimensional (3D) distribution of interstellar dust derived from stellar extinction observations toward the Taurus molecular cloud (MC) and its relation with the neutral atomic hydrogen (HI) emission at 21 cm wavelength and the carbon monoxide $^{12}$CO and $^{13}$CO emission in the $J=1\rightarrow0$ transition. We used the histogram of oriented gradients (HOG) method to match the morphology in a 3D reconstruction of the dust density (3D dust) and the distribution of the gas tracers' emission. The result of the HOG analysis is a map of the relationship between the distances and radial velocities. The HOG comparison between the 3D dust and the HI emission indicates a morphological match at the distance of Taurus but an anti-correlation between the dust density and the HI emission, which uncovers a significant amount of cold HI within the Taurus MC. The HOG between the 3D dust and $^{12}$CO reveals a pattern in radial velocities and distances that is consistent with converging motions of the gas in the Taurus MC, with the near side of the cloud moving at higher velocities and the far side moving at lower velocities. This convergence of flows is likely triggered by the large-scale gas compression caused by the interaction of the Local Bubble and the Per-Tau shell, with Taurus lying at the intersection of the two bubble surfaces.

astro-ph.GA↗

arXiv2022

Disconnecting the Dots: Re-Examining the Nature of Stellar "Strings" in the Milky Way

Recent analyses of Gaia data have resulted in the identification of new stellar structures, including a new class of extended stellar filaments called stellar "strings", first proposed by Kounkel and Covey 2019. We explore the spatial, kinematic, and chemical composition of strings to demonstrate that these newfound structures are largely inconsistent with being physical objects whose members share a common origin. Examining the 3D spatial distribution of string members, we find that the spatial dispersion around the claimed string spine does not improve in the latest Gaia DR3 data release -- despite tangible gains in the signal-to-noise of the parallax measurements -- counter to expectations of a bona fide structure. Using the radial velocity dispersion of the strings (averaging $\rmσ_{V_r} = 16\;km\;s^{-1}$) to estimate their virial masses, we find that all strings are gravitationally unbound. Given the finding that the strings are dispersing, the reported stellar ages of the strings are typically $120\times$ larger than their measured dispersal times. Finally, we validate prior work that stellar strings are more chemically homogeneous than their local field stars, but show it is possible to obtain the same signatures of chemical homogeneity by drawing random samples of stars from spatially, temporally, and kinematically unrelated open clusters. Our results show that while some strings may be composed of real sub-structures, there is no consistent evidence for larger string-like connections over the sample. These results underline the need for caution in over-interpreting the significance of these strings and their role in understanding the star formation history of the Milky Way.

astro-ph.GA↗

arXiv2022

Extending the SAGA Survey (xSAGA) I: Satellite Radial Profiles as a Function of Host Galaxy Properties

We present "Extending the Satellites Around Galactic Analogs Survey" (xSAGA), a method for identifying low-$z$ galaxies on the basis of optical imaging, and results on the spatial distributions of xSAGA satellites around host galaxies. Using spectroscopic redshift catalogs from the SAGA Survey as a training data set, we have optimized a convolutional neural network (CNN) to identify $z < 0.03$ galaxies from more distant objects using image cutouts from the DESI Legacy Imaging Surveys. From the sample of $> 100,000$ CNN-selected low-$z$ galaxies, we identify $>20,000$ probable satellites located between 36-300 projected kpc from NASA-Sloan Atlas central galaxies in the stellar mass range $9.5 < \log(M_\star/M_\odot) < 11$. We characterize the incompleteness and contamination for CNN-selected samples, and apply corrections in order to estimate the true number of satellites as a function of projected radial distance from their hosts. Satellite richness depends strongly on host stellar mass, such that more massive host galaxies have more satellites, and on host morphology, such that elliptical hosts have more satellites than disky hosts with comparable stellar masses. We also find a strong inverse correlation between satellite richness and the magnitude gap between a host and its brightest satellite. The normalized satellite radial distribution between 36-300 kpc does not depend strongly on host stellar mass, morphology, or magnitude gap. The satellite abundances and radial distributions we measure are in reasonable agreement with predictions from hydrodynamic simulations. Our results deliver unprecedented statistical power for studying satellite galaxy populations, and highlight the promise of using machine learning for extending galaxy samples of wide-area surveys.

astro-ph.GA↗