SearcharxivSearch

arXiv subjects

Junnan Shen

Publications and source records attributed to Junnan Shen.

2 recordsLinked to original sources

Dynamical evolution of dark matter subhaloes in the Milky Way: role of the Galactic disc

Dark matter (DM) subhaloes orbiting inside the Milky Way (MW) are promising targets for DM searches, and reliable predictions for the detectability and spatial distribution of their signals are crucial for probing the nature of DM. Recent work showed that tidal forces from the baryonic components of the MW boost the efficiency of subhalo mass-loss, although the underlying physical processes remain insufficiently understood. This study focuses on clarifying the role of the Galactic disc. By using $N$-body simulations, we examine how the dynamical evolution of subhaloes varies with the inclination angle between their orbits and the Galactic disc. Subhaloes whose orbits are inclined by only a few degrees with respect to the Galactic disc pass through it quickly, which enhances tidal shock heating and leads to a pronounced increase in mass-loss efficiency. In contrast, when a subhalo orbit is exactly coplanar with the Galactic disc, adiabatic shielding suppresses the energy input from tidal shocks, resulting in a lower mass-loss efficiency. Tidal stripping lowers the DM density within subhaloes, thereby attenuating the luminosity of their DM signals. Consequently, we expect that subhaloes located at distances of $\sim 0.3$--$2$\,kpc from the Galactic disc plane emit only weak signals, whereas those remaining embedded in the disc are more promising candidates for indirect DM detection, provided that contamination from baryonic emission sources can be carefully modelled and subtracted. Although their mass-loss histories differ significantly, the structural evolution of subhaloes is still well described by the tidal tracks reported in the literature.

astro-ph.CO

Cloud-Aided State Estimation of A Full-Car Semi-Active Suspension System

In this work, we investigate a state estimation problem for a full-car semi-active suspension system. To account for the complex calculation and optimization problems, a vehicle-to- cloud-to-vehicle (V2C2V) scheme is utilized. Moving horizon estimation is introduced for the state estimation system design. All the optimization problems are solved in a remotely-embedded agent with high computational ability. Measurements and state estimates are transmitted between the vehicle and the remote agent via networked communication channels. The effectiveness of the proposed method is illustrated via a set of simulations.

eess.SY