Zhihao Yin | Searcharxiv

arXiv2026

Imprints of tidal interactions on the stellar distribution of satellite galaxies: implications for dark matter deficient galaxies

Interactions with the host galaxy strip stars and dark matter from the outer regions of satellite galaxies. Meanwhile, some stars from the central regions can migrate outward due to dynamical heating, producing an excess in the outer surface brightness relative to the extrapolation of the inner Sérsic profile. Recently discovered dark matter deficient galaxies (DMDGs) appear to be representative examples of such tidally disturbed systems. In this work, we investigate how the break radius, defined as the radius beyond which this surface brightness excess emerges, forms and evolves, by performing $N$-body simulations of a satellite galaxy interacting with a host, where the satellite serves as a plausible progenitor of a DMDG. Our simulations naturally reproduce a break radius consistent with that observed in DMDGs. We find that the break radius grows over time and exhibits a characteristic evolutionary behaviour: during each pericentric passage it briefly contracts due to tidal compression, and then rapidly and strongly expands as the satellite undergoes dynamical relaxation. After the satellite reaches a quasi-equilibrium configuration, the break radius shows only mild variations until the next pericentre. Across our suite of simulations, the ratio of the break radius to the effective radius remains approximately constant, even when we change the orbital parameters and internal structure of the satellite. Based on these findings, we develop a prescription for predicting the time evolution of the break radius, which can be used to constrain the tidal interaction history of satellite galaxies, including DMDGs and splashback galaxies.

astro-ph.GA↗

arXiv2026

Fast Tuning the Index Construction Parameters of Proximity Graphs in Vector Databases

k-approximate nearest neighbor search (k-ANNS) in high-dimensional vector spaces is a fundamental problem across many fields. With the advent of vector databases and retrieval-augmented generation, k-ANNS has garnered increasing attention. Among existing methods, proximity graphs (PG) based approaches are the state-of-the-art (SOTA) methods. However, the construction parameters of PGs significantly impact their search performance. Before constructing a PG for a given dataset, it is essential to tune these parameters, which first recommends a set of promising parameters and then estimates the quality of each parameter by building the corresponding PG and then testing its k-ANNS performance. Given that the construction complexity of PGs is superlinear, building and evaluating graph indexes accounts for the primary cost of parameter tuning. Unfortunately, there is currently no method considered and optimized this process.In this paper, we introduce FastPGT, an efficient framework for tuning the PG construction parameters. FastPGT accelerates parameter estimation by building multiple PGs simultaneously, thereby reducing repeated computations. Moreover, we modify the SOTA tuning model to recommend multiple parameters at once, which can be efficiently estimated using our method of building multiple PGs simultaneously. Through extensive experiments on real-world datasets, we demonstrate that FastPGT achieves up to 2.37x speedup over the SOTA method VDTuner, without compromising tuning quality.

cs.DB↗