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Abstract AstroSage-Llama-3.1-8B is a domain-specialized natural-language AI assistant tailored for research in astronomy, astrophysics, cosmology, and astronomical instrumentation. Trained on the complete collection of astronomy-related arXiv papers from 2007 to 2024 along with millions of synthetically-generated question-answer pairs and other astronomical literature, AstroSage-Llama-3.1-8B demonstrates remarkable proficiency on a wide range of questions. AstroSage-Llama-3.1-8B scores 80.9% on the AstroMLab-1 benchmark, greatly outperforming all models—proprietary and open-weight—in the 8-billion parameter class, and performing on par with GPT-4o. This achievement demonstrates the potential of domain specialization in AI, suggesting that focused training can yield capabilities exceeding those of much larger, general-purpose models. AstroSage-Llama-3.1-8B is freely available, enabling widespread access to advanced AI capabilities for astronomical education and research. 

Abstract We introduce the Phoenix Simulations, a suite of highly resolved cosmological simulations featuring hydrodynamics, primordial gas chemistry, primordial and enriched star formation and feedback, UV radiative transfer, and saved outputs with Δt= 200 kyr. We observe 73,523 individual primordial stars within 3313 distinct regions forming 2110 second-generation enriched star clusters byz≥ 12 within a combined 177.25 Mpc³volume across three simulations. The regions that lead to enriched star formation can contain ≳150 primordial stars, with 80% of regions having experienced combinations of primordial Type II, hypernovae, and/or pair-instability supernovae. Primordial supernovae enriched 0.8% of the volume, with 2% of enriched gas enriched by later-generation stars. We determine the extent of a primordial stellar region by its metal-rich or ionized hydrogen surrounding cloud; the metal-rich and ionized regions have time-dependent average radiir≲ 3kpc. 7 and 17% of regions haver> 7 kpc for metal-rich and ionized radii, respectively. We find that the metallicity distribution function of second-generation stars overlaps that of subsequent Population II star formation, spanning metal-deficient (∼7.94 × 10⁻⁸Z_⊙) to supersolar (∼3.71Z_⊙), and that 30.5% of second-generation stars haveZ> 10⁻²Z_⊙. We find that the metallicity of second-generation stars depends on progenitor configuration, with metals from pair-instability supernovae contributing to the most metal-rich clusters; these clusters form promptly after the supernova event. Finally, we create an interpretable regression model to predict the radius of the metal-rich influence of Population III star systems within the first 7–18 Myr after the first Population III stars form in the region.