arXiv subjects

Ruoyun Huang

Publications and source records attributed to Ruoyun Huang.

8 recordsLinked to original sources

arXiv2026

Chemical Abundances and Globular Clusters of Milky Way Dwarf Galaxies

We present an overview of our ongoing GASTRONOMI project, which investigates the coevolution of the Milky Way (MW), its satellite dwarf galaxies, and their star clusters through chemo-dynamical analysis. We derive precise chemical abundances for stars in five classical dwarf galaxies, which reveal mass-dependent chemical evolution, particularly in alpha elements, such as [Si/Fe]. A distinct dichotomy in [Al/Fe] is found between metal-rich ([Fe/H]>-1.5) stars formed in-situ in the MW and those originating in dwarf galaxies. Star clusters act as sensitive environmental probes. The presence of multiple populations correlates with galactic evolution, and nitrogen-rich stars in Fornax are likely relics of disrupted globular clusters (GCs). We developed a chemical classification for Galactic GCs, isolating primordial populations by their low [Al/Fe]. This places in-situ and accreted GCs in distinct regions of the [Al/Fe]-[Fe/H] plane, providing a new tool to reconstruct the Galaxy's accretion history.

astro-ph.GA↗

arXiv2026

A Tale of Two Origins: In-Situ versus Accreted Nitrogen-Rich Field Stars in the MW

Spectroscopic surveys have identified significant numbers of metal-poor nitrogen-rich (N-rich) field stars. These stars are strong candidates for escapees from globular clusters (GCs), as their distinctive nitrogen enhancement mirrors the chemical patterns observed in some of the members of GCs. As part of the effort to characterize their chemodynamical properties, we derived abundances for up to 25 elements in a sample of 33 N-rich field giant stars (18 of them are studied for the first time) using high-resolution optical spectroscopy. We confirm their elevated abundances of N, Na, and Al, strongly supporting a GC origin. Given that Galactic GCs themselves formed within diverse progenitor galaxies, we sought to identify the ancestral systems of these N-rich field stars. By analyzing their dynamical parameters, we separated the sample into high-energy (HE) and low-energy (LE) groups. The HE group exhibits lower [{\alpha}/Fe] and enhanced r-process abundances compared to the LE group. This indicates that the HE stars likely escaped from GCs accreted from massive dwarf galaxies (e.g., Gaia-Sausage-Enceladus), while the LE stars probably originated from in-situ GCs. We also find that the chemical pattern of these N-rich stars with [Fe/H] {\lessapprox} -1.0 are similar to the high-redshift ''N-emitters''. Furthermore, orbital integrations revealed a close encounter between one N-rich field star and the globular cluster NGC 6235. Our work demonstrates the potential of using chemodynamical analyses to trace Galactic assembly through chemical peculiar stars, while highlighting that larger samples and more precise data in the future are crucial to establish definitive origins.

astro-ph.GA↗

arXiv2026

Spatial Property of Multiple Metallic Populations in the Tidal Stream of {\omega} Centauri

{\omega} Centauri, the remnant nucleus of an accreted dwarf galaxy, is a unique laboratory for studying complex stellar populations. The recently discovered Fimbulthul stream provides a fossil record of its ongoing tidal dissolution. In this work, we investigate the spatial distributions of metal-rich and metal-poor populations within {\omega} Centauri and its stream to constrain the cluster's formation history. Using synthetic photometry from Gaia DR3 XP spectra, we classify stars via a Support Vector Classifier (SVC). The spatial distributions are then compared to a scaling N-body simulation performed with the PeTar code. Our analysis reveals no significant radial gradient in population ratios within the cluster, though the metal-rich stars may be slightly more extended. The population ratio in the tidal stream is consistent with that of the present-day cluster, albeit with large uncertainties. Our simulation indicates that any initial radial gradient must have been shallow, with a maximum fraction difference less than 0.15. Both observational and dynamical results suggest that the metal-rich population is not formed centrally concentrated. By combining our results and existing literature, we propose a new formation scenario for {\omega} Centauri.

astro-ph.GA↗

arXiv2024

GraphScale: A Framework to Enable Machine Learning over Billion-node Graphs

Graph Neural Networks (GNNs) have emerged as powerful tools for supervised machine learning over graph-structured data, while sampling-based node representation learning is widely utilized in unsupervised learning. However, scalability remains a major challenge in both supervised and unsupervised learning for large graphs (e.g., those with over 1 billion nodes). The scalability bottleneck largely stems from the mini-batch sampling phase in GNNs and the random walk sampling phase in unsupervised methods. These processes often require storing features or embeddings in memory. In the context of distributed training, they require frequent, inefficient random access to data stored across different workers. Such repeated inter-worker communication for each mini-batch leads to high communication overhead and computational inefficiency. We propose GraphScale, a unified framework for both supervised and unsupervised learning to store and process large graph data distributedly. The key insight in our design is the separation of workers who store data and those who perform the training. This separation allows us to decouple computing and storage in graph training, thus effectively building a pipeline where data fetching and data computation can overlap asynchronously. Our experiments show that GraphScale outperforms state-of-the-art methods for distributed training of both GNNs and node embeddings. We evaluate GraphScale both on public and proprietary graph datasets and observe a reduction of at least 40% in end-to-end training times compared to popular distributed frameworks, without any loss in performance. While most existing methods don't support billion-node graphs for training node embeddings, GraphScale is currently deployed in production at TikTok enabling efficient learning over such large graphs.

cs.LG↗

arXiv2024

Driving factors behind multiple populations

Star clusters were historically considered simple stellar populations, with all stars sharing the same age and initial chemical composition. However, the presence of chemical anomalies in globular clusters (GCs), called multiple stellar populations (MPs), has challenged star formation theories in dense environments. Literature studies show that mass, metallicity, and age are likely controlling parameters for the manifestation of MPs. Identifying the limit between clusters with/without MPs in physical parameter space is crucial to reveal the driving mechanism behind their presence. In this study, we look for MP signals in Whiting 1, traditionally considered a young GC. Using the Magellan telescope, we obtained low-resolution spectra within $\rm λλ= 3850-5500 Å$ for eight giants of Whiting 1. We measured the C and N abundances from the CN and CH spectral indices. C and N abundances have variations comparable with their measurement errors ($\sim0.1$ dex), suggesting that MPs are absent from Whiting 1. Combining these findings with literature studies, we propose a limit in the metallicity vs. cluster compactness index parameter space, which relatively clearly separates star clusters with/without MPs (GCs/open clusters). This limit is physically motivated. On a larger scale, the galactic environment determines cluster compactness and metallicity, leading to metal-rich, diffuse, old clusters formed ex situ. Our proposed limit also impacts our understanding of the formation of the Sagittarius dwarf galaxy: star clusters formed after the first starburst (age$\lesssim 8-10$ Gyr). These clusters are simple stellar populations because the enriched galactic environment is no longer suitable for MP formation.

astro-ph.GA↗

arXiv2020

Multiple populations in low mass globular clusters: Palomar 13

Since the discovery of chemically peculiar stars in globular clusters in the last century, the study of multiple populations has become increasingly important, given that chemical inhomogeneity is found in almost all globular clusters. Despite various proposed theories attempting to explain this phenomenon, fitting all the observational evidence in globular clusters with one single theory remains notoriously difficult and currently unsuccessful. In order to improve existing models and motivate new ones, we are observing globular clusters at critical conditions, e.g., metal-rich end, metal-poor end, and low mass end. In this paper, we present our first attempt to investigate multiple populations in low mass globular clusters. We obtained low-resolution spectra around 4000 A of 30 members of the globular cluster Palomar 13 using OSIRIS/Multi-object spectrograph mounted at the Gran Telescopio Canarias. The membership of red giant branch stars is confirmed by the latest proper motions from Gaia DR2 and literature velocities. After comparing the measured CN and CH spectral indices with those of the stellar models, we found a clear sign of nitrogen variation among the red giant branch stars. Palomar 13 may be the lowest mass globular cluster showing multiple populations.

astro-ph.GA↗

arXiv2014

SAS+ Planning as Satisfiability

Planning as satisfiability is a principal approach to planning with many eminent advantages. The existing planning as satisfiability techniques usually use encodings compiled from STRIPS. We introduce a novel SAT encoding scheme (SASE) based on the SAS+ formalism. The new scheme exploits the structural information in SAS+, resulting in an encoding that is both more compact and efficient for planning. We prove the correctness of the new encoding by establishing an isomorphism between the solution plans of SASE and that of STRIPS based encodings. We further analyze the transition variables newly introduced in SASE to explain why it accommodates modern SAT solving algorithms and improves performance. We give empirical statistical results to support our analysis. We also develop a number of techniques to further reduce the encoding size of SASE, and conduct experimental studies to show the strength of each individual technique. Finally, we report extensive experimental results to demonstrate significant improvements of SASE over the state-of-the-art STRIPS based encoding schemes in terms of both time and memory efficiency.

cs.AI↗

arXiv2011

Theory and Algorithms for Partial Order Based Reduction in Planning

Search is a major technique for planning. It amounts to exploring a state space of planning domains typically modeled as a directed graph. However, prohibitively large sizes of the search space make search expensive. Developing better heuristic functions has been the main technique for improving search efficiency. Nevertheless, recent studies have shown that improving heuristics alone has certain fundamental limits on improving search efficiency. Recently, a new direction of research called partial order based reduction (POR) has been proposed as an alternative to improving heuristics. POR has shown promise in speeding up searches. POR has been extensively studied in model checking research and is a key enabling technique for scalability of model checking systems. Although the POR theory has been extensively studied in model checking, it has never been developed systematically for planning before. In addition, the conditions for POR in the model checking theory are abstract and not directly applicable in planning. Previous works on POR algorithms for planning did not establish the connection between these algorithms and existing theory in model checking. In this paper, we develop a theory for POR in planning. The new theory we develop connects the stubborn set theory in model checking and POR methods in planning. We show that previous POR algorithms in planning can be explained by the new theory. Based on the new theory, we propose a new, stronger POR algorithm. Experimental results on various planning domains show further search cost reduction using the new algorithm.

cs.AI↗