SearcharxivSearch

arXiv subjects

Tingting Tian

Publications and source records attributed to Tingting Tian.

2 recordsLinked to original sources

Recovering the infall mass for Milky Way satellite galaxy Sextans

Understanding the formation and evolution of the Milky Way (MW) requires detailed knowledge of its satellite galaxies. In this study, we focus on the Sextans dwarf spheroidal (dSph) galaxy, a faint, dark matter (DM)-dominated satellite, to investigate the role of tidal and baryonic effects in shaping its observed properties. Using tailored $N$-body simulations, we explore possible orbits of Sextans in different MW models to reconstruct its progenitor's properties. Our simulations demonstrate the stars in Sextans are only mildly affected by galactic tides and the stellar kinematics provide robust constraints on its dynamical mass within the half-light radius, while the tidal mass loss of its DM component depends primarily on MW mass. The recovered infall mass of Sextans ranges from $1.22$ to $3.14\times10^9\rm\,M_\odot$ for MW masses from $0.8$ to $2\times10^{12}\rm\,M_\odot$. If the DM density remained as cuspy as NFW profile, the infall mass would be smaller by a factor of 2. Although with large ranges, the possible infall masses of Sextans recovered by our simulations are consistent with the stellar mass-halo mass relation in TNG50 and abundance matching results. We find some cases for the cuspy DM density profile where the infall mass is smaller than $10^9\rm\,M_\odot$, possibly indicating that star formation in Sextans is more efficient than in other satellites. The recovered DM halo structural parameters from our simulations provide valuable constraints for future studies on the DM content and formation history of Sextans.

astro-ph.GA

Nonlinear model reference adaptive control approach for governance of the commons in a feedback-evolving game

The governance of common-pool resources has vital importance for sustainability. However, in the realistic management systems of common-pool resources, the institutions do not necessarily execute the management policies completely, which will induce that the real implementation intensity is uncertain. In this paper, we consider a feedback-evolving game model with the inspection for investigating the management of renewable resource and assume that there exists the implementation uncertainty of inspection. Furthermore, we use the nonlinear model reference adaptive control approach to handle this uncertainty. We accordingly design a protocol, which is an update law of adjusting the institutional inspection intensity. We obtain a sufficient condition under which the update law can drive the actual system to reach the expected outcome. In addition, we provide several numerical examples, which can confirm our theoretical results. Our work presents a novel approach to address the implementation uncertainty in the feedback-evolving games and thus our results can be helpful for effectively managing the common-pool resources in the human social systems.

math.DS