arXiv subjects
Publications and source records attributed to Jennifer Lynn Bartlett.
For decades, the NASA Astrophysics Data System (ADS) has been the foundational digital library for astronomy. As ADS becomes the Science Explorer (SciX), the team prioritizes preserving this trusted experience while increasing their support for space and Earth sciences broadly, without diluting its commitment to astrophysics.
Scientific multi-label text classification suffers from extreme class imbalance, where specialized terminology exhibits severe power-law distributions that challenge standard classification approaches. Existing scientific corpora lack comprehensive controlled vocabularies, focusing instead on broad categories and limiting systematic study of extreme imbalance. We introduce AstroConcepts, a corpus of English abstracts from 21,702 published astrophysics papers, labeled with 2,367 concepts from the Unified Astronomy Thesaurus. The corpus exhibits severe label imbalance, with 76% of concepts having fewer than 50 training examples. By releasing this resource, we enable systematic study of extreme class imbalance in scientific domains and establish strong baselines across traditional, neural, and vocabulary-constrained LLM methods. Our evaluation reveals three key patterns that provide new insights into scientific text classification. First, vocabulary-constrained LLMs achieve competitive performance relative to domain-adapted models in astrophysics classification, suggesting a potential for parameter-efficient approaches. Second, domain adaptation yields relatively larger improvements for rare, specialized terminology, although absolute performance remains limited across all methods. Third, we propose frequency-stratified evaluation to reveal performance patterns that are hidden by aggregate scores, thereby making robustness assessment central to scientific multi-label evaluation. These results offer actionable insights for scientific NLP and establish benchmarks for research on extreme imbalance.
We present our participation in the SOMD 2026 shared task on cross-document software mention coreference resolution, where our systems ranked second across all three subtasks. We compare two fine-tuning-free approaches: Fuzzy Matching (FM), a lexical string-similarity method, and Context Aware Representations (CAR), which combines mention-level and document-level embeddings. Both achieve competitive performance across all subtasks (CoNLL F1 of 0.94-0.96), with CAR consistently outperforming FM by 1 point on the official test set, consistent with the high surface regularity of software names, which reduces the need for complex semantic reasoning. A controlled noise-injection study reveals complementary failure modes: as boundary noise increases, CAR loses only 0.07 F1 points from clean to fully corrupted input, compared to 0.20 for FM, whereas under mention substitution, FM degrades more gracefully (0.52 vs. 0.63). Our inference-time analysis shows that FM scales superlinearly with corpus size, whereas CAR scales approximately linearly, making CAR the more efficient choice at large scale. These findings suggest that system selection should be informed by both the noise profile of the upstream mention detector and the scale of the target corpus. We release our code to support future work on this underexplored task.
As astronomy enters an era defined by global telescope networks, petabyte-scale surveys, and powerful computational tools, the longstanding goals of astronomy education, particularly introductory ``ASTRO101'', but equally encompassing both higher and lower level courses, warrant fresh examination. In June 2024, the AstroEdUNC meeting at UNC--Chapel Hill convened 100 astronomers, education researchers, and practitioners to synthesise community perspectives on the purpose, content, and delivery of astronomy education. Beginning with historical vignettes, the meeting's deliberations were organised into six interrelated themes: (1) Context, highlighting astronomy's evolution from classical charting to multi-messenger discovery and its role as a connective thread across STEM and the humanities; (2) Content, exploring how curricula can balance essential concepts with authentic investigations and leverage open-source and AI-augmented resources; (3) Skills, arguing that astronomy should foreground scientific literacy, computational fluency, and communication through genuine data-driven inquiry; (4) Engagement, advocating for active-learning strategies, formative assessment, and culturally inclusive narratives; (5) Beyond the Classroom, emphasising scaffolding, universal-design practices, and K--12/community partnerships; and (6) Astronomy Education Research, outlining priority areas for assessing knowledge, attitudes, and long-term outcomes. We provide concrete recommendations for future astronomy education research development, underscoring the need for approaches to education that are authentic while meeting the learning and life goal needs of the students, a vibrant community of practice and robust researcher-practitioner partnerships to ensure that introductory astronomy is pertinent, applicable and inspiring to a broad student population.
We argue that it is essential that the Astro2020 survey of the present state of American astronomy and the recommendations for the next decade address the issue of ensuring preservation of, and making more discoverable and accessible, the field's rich legacy materials. These include both archived observations of scientific value and items of historical importance. Much of this heritage likely will be lost if action is not taken in the next decade. It is proposed that the decadal plan include recommendations on (1) compiling a list of historic sites and development of models for their preservation, (2) carrying out a comprehensive inventory of astronomy's archival material, and (3) digitizing, with web-based publication, those photographs and papers judged to have the most value for scientific and historical investigations. The estimated cost for an example project on plate preservation is a one-time investment of less than $10 million over ten years plus the typical on-going costs to maintain and manage a medium-sized database.
Gaia is currently revolutionizing modern astronomy. However, much of the Galactic plane, center and the spiral arm regions are obscured by interstellar extinction, rendering them inaccessible because Gaia is an optical instrument. An all-sky near infrared (NIR) space observatory operating in the optical NIR, separated in time from the original Gaia would provide microarcsecond NIR astrometry and millimag photometry to penetrate obscured regions unraveling the internal dynamics of the Galaxy.
Over the past decades and even centuries, the astronomical community has accumulated a signif-icant heritage of recorded observations of a great many astronomical objects. Those records con-tain irreplaceable information about long-term evolutionary and non-evolutionary changes in our Universe, and their preservation and digitization is vital. Unfortunately, most of those data risk becoming degraded and thence totally lost. We hereby call upon the astronomical community and US funding agencies to recognize the gravity of the situation, and to commit to an interna-tional preservation and digitization efforts through comprehensive long-term planning supported by adequate resources, prioritizing where the expected scientific gains, vulnerability of the origi-nals and availability of relevant infrastructure so dictates. The importance and urgency of this issue has been recognized recently by General Assembly XXX of the International Astronomical Union (IAU) in its Resolution B3: "on preservation, digitization and scientific exploration of his-torical astronomical data". We outline the rationale of this promotion, provide examples of new science through successful recovery efforts, and review the potential losses to science if nothing it done.
Despite the continuing importance of ground-based parallax measurements, few active programs remain. Because new members of the solar neighborhood tend towards later spectral types, infrared parallax programs are particularly desirable. Consequently, the astrometric quality of the new infrared camera, FanCam, developed by the Virginia Astronomical Instrumentation Laboratory (VAIL) for the 31-in (0.8-m) Tinsley reflector at Fan Mountain Observatory was assessed using 68 J-band exposures of an open cluster, NGC 2420, over a range of hour angles during 2005. Positions of 16 astrometric evaluation stars were measured and the repeatability of those positions was evaluated using the mean error in a single observation of unit weight. Overall, a precision of 1.3 +/- 0.7 microns in x (RA) and 1.3 +/- 0.8 microns in y (Dec) was attained, which corresponds to 0.04" +/- 0.02" in each axis. Although greater precision is expected from CCDs in the visual and near-infrared, this instrument can achieve precision similar to that of the ESO NTT infrared parallax program. Therefore, measuring parallaxes in the infrared would be feasible using this equipment. If initiated, such a program could provide essential distances for brown dwarfs and very low mass stars that would contribute significantly to the solar neighborhood census.