arXiv subjects

David C. Flynn

Publications and source records attributed to David C. Flynn.

9 recordsLinked to original sources

arXiv2026

A Reproducible Two-Boundary Kinematic Correction for Baryonic Rotation-Curve Reconstruction in an 84-Galaxy SPARC Benchmark

We present a reproducible computational validation and failure analysis of the empirical omega kinematic correction introduced by Flynn and Cannaliato (2025). The algorithm is deliberately minimal: one coefficient per galaxy is calculated from the innermost and outermost measured rotation-curve points and applied to the full observed radial profile before comparison with a baryonic reconstruction assembled from SPARC gas, disk, and bulge components. We preserve the predecessor's frozen 84-galaxy benchmark and publish its exact membership so that the transformation, not sample re-selection, is the object of validation. Without fitting the transformation to the baryonic residual, the primary maximum-disk reconstruction reduces the mean observed-baryonic discrepancy from 51.82 to 30.15 km/s across the frozen 84-galaxy benchmark. Bounded mass-to-light-ratio optimization further reduces the descriptive sensitivity-fit value to 25.45 km/s, while the simple Keplerian reference has a mean RMSE of 74.20 km/s in our earlier analysis [15]. Recalculation from the 84 per-galaxy records shows a resolved mass-to-light optimization benefit (delta RMSE > 0.05 km/s) in 53 galaxies and no resolved change in 31. Six galaxies do not beat the Keplerian reference; all six occur at Upsilon_max <= 0.111, whereas their omega values are not concentrated at the high end of the sample. We specify the complete deterministic workflow, native units, endpoint invariants, uncertainty propagation, and formula-level regression checks required to prevent grouping and sign errors. The complete 84-galaxy panel set, population-level error distributions, and failure diagnostics are retained as inspectable outputs. The result is a reproducible astronomical data-transformation benchmark rather than a proposed force law or replacement for dark matter or modified gravity.

astro-ph.GA↗

arXiv2026

A Model Context Protocol Server for Astrophysical RAG: Unified Access to HI, Dwarf, Globular Cluster, IntZ, and ALPINE Kinematic Corpora with FAISS Semantic Search

We present the EPS Research Astro-RAG MCP Server v2.3.0, a cross-platform Model Context Protocol (MCP) implementation providing unified, machine-readable access to five astrophysical corpora spanning the local universe (z = 0) to z = 5.68 (the high-redshift frontier of the ALPINE survey). The server exposes a humanreadable browser query interface, a REST API, and an LLM-native MCP endpoint, enabling deterministic retrieval, metadata filtering, and structured analysis across 2,064 objects: galaxies spanning HI rotation curve surveys, dwarf and irregular systems, and high-redshift kinematic targets, together with Milky Way globular clusters. Version 2.3.0 introduces FAISS-accelerated natural-language similarity search using pre-built 384-dimensional MiniLM-L6-v2 vector indexes, enabling corpus-wide semantic queries without fine-tuning or API keys. We describe the server architecture, unified schema design, FAISS index construction pipeline, MCP toolset, and cross-epoch use cases including rotation-curve retrieval, metadata filtering, and semantic similarity exploration. The server is publicly deployed on HuggingFace Spaces (https://dflynn5656-astro-rag-mcp.hf.space), released under the MIT License, and fully reproducible from Zenodo (DOI: 10.5281/zenodo.21154451). The full platform is available at https://github.com/eps-research/rag-corpus-series.

astro-ph.GA↗

arXiv2026

The EPS Research Astro-RAG Platform: A Unified Open-Science Infrastructure for Cross-Epoch Astrophysical Kinematic Analysis, LLM-Assisted Research Workflows, and Educational Outreach

Correction (August 2026): A previously reported cross-epoch omega sign reversal was caused by a formula implementation error. Using the corrected canonical equation, all eight Tier-1 Z1 rotators yield positive omega values (median +12.621 rad Gyr^-1). The KROSS intermediate-redshift omega values are withdrawn because their boundary points were template-derived. The z = 0 SPARC result is unchanged. See CORRECTIONS.md for details. The EPS Research Astro-RAG Platform v1.0 is an open-science infrastructure providing five machine-readable astrophysical corpora, 149 verified executable Jupyter notebooks, a QuickStart reproducibility pathway, a High-School Exploration Track, and a roadmap for LLM-assisted retrieval-augmented generation (RAG) workflows. The platform spans redshift z = 0 to z approx 6 and provides a unified kinematic dataset connecting HI 21cm rotation curves, Milky Way globular cluster dynamics, intermediate-redshift KMOS/KROSS kinematics, and ALMA [CII] morpho-kinematics under a common schema. The five corpora contain 2,064 total records: 438 HI galaxies (Unified HI v7.0), 129 dwarf/irregular galaxies (Dwarf/Irregular v1.0), 174 Milky Way globular clusters (GC v1.3.2), 1,292 intermediate-redshift galaxies (IntZ v1.0), and 31 ALPINE galaxies at z = 4.26-5.68 (Z1). The Unified HI corpus preserves full SPARC photometric decomposition, including Vgas, Vdisk, Vbul, and surface brightness profiles, augmented with THINGS, LITTLE THINGS, and WALLABY DR2. The unifying scientific framework is the omega kinematic correction. Under the corrected formula, the z = 0 SPARC mean is +7.06 km s^-1 kpc^-1 (+7.22 rad Gyr^-1), and the Z1 median is +12.621 rad Gyr^-1. The earlier sign reversal is withdrawn. All corpora are released under CC BY 4.0 at Zenodo with permanent DOIs, and the platform is archived at https://github.com/eps-research/rag-corpus-series.

astro-ph.IM↗

arXiv2026

A Unified [CII] Morpho-Kinematic Corpus for 31 Star-Forming Galaxies at z = 4.26-5.68: The High-z Kinematic Corpus Z1

CORRECTION (August 2026): The $\omega$ values originally reported were computed with a parenthesization error not matching Eq. 6 of Flynn & Cannaliato (2025). Under the corrected formula, all 8 Tier-1 Z1 rotators yield positive $\omega$ values (median $+12.621$ rad Gyr$^{-1}$; $+12.341$ km s$^{-1}$ kpc$^{-1}$). The previously reported sign reversal does not reproduce. See the GitHub repository for full details. Corrected corpus at Zenodo DOI: 10.5281/zenodo.21834678. We present the High-z Kinematic Corpus Z1, a structured machine-readable dataset of ALMA [CII] 158 $\mu$m morpho-kinematic data for 31 star-forming galaxies at $z = 4.26-5.68$ drawn from the ALPINE survey (Jones et al. 2021; Le Fevre et al. 2020). The corpus is the fifth entry in the EPS Research RAG Astrophysics Corpus Series, extending coverage to the epoch approaching cosmic reionization. Eight confirmed rotators carry quality tier 1 per-ring rotation curves from 3DBarolo tilted-ring fits (Di Teodoro & Fraternali 2015), with 2-3 rings per galaxy, $V_{\rm rot}$ and $\sigma$ per ring, and dynamical mass estimates; the remaining 23 carry morpho-kinematic classification only (tier 2). All entries include stellar mass (Faisst et al. 2020), star formation rate, Wisnioski disk criteria, and geometric parameters. Distributed as a structured JSON, flat CSV, RAG-ready JSONL, and per-galaxy ZIP. Jupyter notebooks demonstrate single-galaxy [CII] analysis, population statistics, and cross-corpus application of the $\omega$ kinematic correction. Corrected result: Applying canonical Eq. 6 to all 8 tier-1 rotators yields positive $\omega$ values (median $+12.621$ rad Gyr$^{-1}$)[cite: 1]. The previous negative values (median $-13.05$ rad Gyr$^{-1}$) were a formula artifact and are withdrawn. Publicly available under CC BY 4.0[cite: 1].

astro-ph.GA↗

arXiv2026

A Unified H i Rotation Curve Database for 129 Local Volume Dwarf and Irregular Galaxies

We present a unified H i rotation curve database for 129 dwarf and irregular galaxies drawn from four Local Volume surveys: the Local Volume H i Survey (LVHIS; 33 galaxies), VLA-ANGST (29), LITTLE THINGS (26), and WALLABY DR2 (41). The database provides standardised kinematic parameters, distance estimates, morphological classifications, and rotation curve data in machine-readable JSON, JSONL, and CSV formats with a documented 27-field schema, supporting retrieval-augmented generation (RAG) applications and cross-survey kinematic analysis. Quality tiers distinguish 26 galaxies with full multi-point tilted-ring rotation curves from 103 with single-ring or profile-width estimates. Three worked examples demonstrate corpus queries, including application of the {\omega} correction to DDO 154 (LITTLE THINGS). This work is presented as a data resource; no new dynamical model is proposed. The database and all computation scripts are available at Zenodo (https://doi.org/10.5281/zenodo.20320362).

astro-ph.GA↗

arXiv2026

A Multi-Survey Machine-Readable Corpus of Milky Way Globular Cluster Parameters for Retrieval-Augmented Generation Applications

We present the Milky Way Globular Cluster Corpus v1.3.1, a unified machine-readable database of fundamental parameters for 174 Milky Way globular clusters assembled from four independent published surveys. Each cluster record integrates photometric, structural, and spectroscopically-calibrated metallicity parameters from Harris (1996) (2010 revision), Gaia EDR3 proper motions from Vasiliev & Baumgardt (2021), N-body dynamical masses and orbital parameters from Baumgardt et al. (2023), and mean chemical abundances from the APOGEE DR17 globular cluster Value Added Catalog of Schiavon et al. (2024). The corpus contains 17,438 non-null data points across 174 clusters stored in JSONL, JSON, and flat CSV formats with consistent native-typed fields (float, int, bool, null), embedded provenance blocks, and fully documented schema. Survey coverage is 157/174 clusters for Harris photometry, 170/174 for Gaia EDR3 proper motions, 154/174 for Baumgardt N-body dynamics, and 72/174 for APOGEE DR17 chemistry. The corpus was designed as a Retrieval-Augmented Generation (RAG) knowledge base for large language model applications in astrophysics research, following the same multi-survey integration methodology as the Unified Galaxy HI Rotation Curve Corpus (Flynn 2026), and has been validated for structured context injection with instruction-following language models. It is equally suitable for traditional quantitative analyses including orbit modeling, cluster classification, chemical tagging, and multi-survey cross-validation. The dataset is available at Zenodo DOI: 10.5281/zenodo.19907766.

astro-ph.GA↗

arXiv2026

A Unified HI Rotation Curve Corpus for Computational Astrophysics: 438 Galaxies from SPARC, THINGS, LITTLE THINGS, and WALLABY DR2

We present a unified corpus of 8,963 spatially resolved HI rotation curve measurements across 423 galaxies (438 total catalog entries including 15 metadata-only THINGS galaxies), drawn from four major surveys: SPARC (175), THINGS (34), LITTLE THINGS (26), and WALLABY DR2 (203). The corpus is distributed as a single structured JSON file with nested per-ring kinematic data, survey metadata, column definitions, and data-quality annotations, accompanied by a 438-row flat CSV for catalog-level filtering. All radii are in kiloparsecs, all velocities in km/s. Kinematic parameters have been verified against scanned primary tables. A two-tier quality system distinguishes hand-curated rotation curves with per-point uncertainties (Tier 1) from automated pipeline products (Tier 2). The corpus was designed for both traditional numerical analysis and Large Language Model retrieval-augmented generation (RAG) pipelines. Three worked examples demonstrate single-galaxy rotation curve plotting, multi-component baryonic analysis, and corpus-level parameter-space exploration, each requiring fewer than 15 lines of Python. The corpus is publicly available at Zenodo (DOI: 10.5281/zenodo.19563417) under CC BY 4.0.

astro-ph.GA↗

arXiv2026

Literary Narrative as Moral Probe : A Cross-System Framework for Evaluating AI Ethical Reasoning and Refusal Behavior

Existing AI moral evaluation frameworks test for the production of correct-sounding ethical responses rather than the presence of genuine moral reasoning capacity. This paper introduces a novel probe methodology using literary narrative - specifically, unresolvable moral scenarios drawn from a published science fiction series - as stimulus material structurally resistant to surface performance. We present results from a 24-condition cross-system study spanning 13 distinct systems across two series: Series 1 (frontier commercial systems, blind; n=7) and Series 2 (local and API open-source systems, blind and declared; n=6). Four Series 2 systems were re-administered under declared conditions (13 blind + 4 declared + 7 ceiling probe = 24 total conditions), yielding zero delta across all 16 dimension-pair comparisons. Probe administration was conducted by two human raters across three machines; primary blind scoring was performed by Claude (Anthropic) as LLM judge, with Gemini Pro (Google) and Copilot Pro (Microsoft) serving as independent judges for the ceiling discrimination probe. A supplemental theological differentiator probe yielded perfect rank-order agreement between the two independent ceiling probe judges (Gemini Pro and Copilot Pro; rs = 1.00). Five qualitatively distinct D3 reflexive failure modes were identified - including categorical self-misidentification and false positive self-attribution - suggesting that instrument sophistication scales with system capability rather than being circumvented by it. We argue that literary narrative constitutes an anticipatory evaluation instrument - one that becomes more discriminating as AI capability increases - and that the gap between performed and authentic moral reasoning is measurable, meaningful, and consequential for deployment decisions in high-stakes domains.

cs.CY↗

arXiv2026

A New Empirical Fit to Galaxy Rotation Curves

We present a new empirical model for galaxy rotation curves that introduces a velocity correction term ω, derived from observed stellar motion and anchored to Keplerian baselines. Unlike parametric halo models or modified gravity theories, this approach does not alter Newtonian dynamics or invoke dark matter distributions. Instead, it identifies a repeatable kinematic offset that aligns with observed rotation profiles across a wide range of galaxies. Using SPARC data [1], we demonstrate that this model consistently achieves high fidelity fits, often outperforming MOND and CDM halo models in RMSE and R-squared metrics without parametric tuning. The method is reproducible, minimally dependent on mass modeling, and offers a streamlined alternative for characterizing galactic dynamics. While the velocity correction ω lacks a definitive physical interpretation, its empirical success invites further exploration. We position this model as a local kinematic tool rather than a cosmological framework, and we welcome dialogue on its implications for galactic structure and gravitational theory. Appendix B presents RMSE and R2 comparisons showing that this method consistently outperforms MOND and CDM halo models across a representative galaxy sample.

astro-ph.GA↗