Tianru Li

We report the discovery of Pegasus IV, an ultra-faint dwarf galaxy found in archival data from the Dark Energy Camera processed by the DECam Local Volume Exploration Survey. Pegasus IV is a compact, ultra-faint stellar system ($r_{1/2} = 41^{+8}_{-6}$ pc; $M_V = -4.25 \pm 0.2$ mag) located at a heliocentric distance of $90^{+4}_{-6}$ kpc. Based on spectra of seven non-variable member stars observed with Magellan/IMACS, we confidently resolve Pegasus IV's velocity dispersion, measuring $\sigma_{v} = 3.3^{+1.7}_{-1.1} \text{ km s}^{-1}$ (after excluding three velocity outliers); this implies a mass-to-light ratio of $M_{1/2}/L_{V,1/2} = 167^{+224}_{-99} M_{\odot}/L_{\odot}$ for the system. From the five stars with the highest signal-to-noise spectra, we also measure a systemic metallicity of $\rm [Fe/H] = -2.67^{+0.25}_{-0.29}$ dex, making Pegasus IV one of the most metal-poor ultra-faint dwarfs. We tentatively resolve a non-zero metallicity dispersion for the system. These measurements provide strong evidence that Pegasus IV is a dark-matter-dominated dwarf galaxy, rather than a star cluster. We measure Pegasus IV's proper motion using data from Gaia Early Data Release 3, finding ($\mu_{\alpha*}, \mu_{\delta}) = (0.33\pm 0.07, -0.21 \pm 0.08) \text{ mas yr}^{-1}$. When combined with our measured systemic velocity, this proper motion suggests that Pegasus IV is on an elliptical, retrograde orbit, and is currently near its orbital apocenter. Lastly, we identify three potential RR Lyrae variable stars within Pegasus IV, including one candidate member located more than ten half-light radii away from the system's centroid. The discovery of yet another ultra-faint dwarf galaxy strongly suggests that the census of Milky Way satellites is still incomplete, even within 100 kpc.

At the beginning of the 2020s, computing is moving into a new phase from a centralized model to a decentralized one. The first shift from centralized computing to decentralized computing in 1980 was due to personal computing, which formed a foundation for the decentralization method. Since mid-2000, the centralized cloud computing has begun its rise to the outstanding position. Driven by the flourishing of IoT, many new issues have arisen, such as unprecedented data volume, latency control, bandwidth efficiency, reliability of service, and sustainability. These issues limit the development of latency-sensitive IoT-based applications such as unmanned autonomous vehicles (UAV), Machine to Machine (M2M) communications. Hence, various emerging edge-based computing models have been proposed to address these issues related to the post-cloud. This paper first reviews the concepts and challenges of cloud computing. It then explores the driving force from IoT technologies and reveals the relationship between the flourish of IoT and the emerging of post-cloud computing. It also compares several fundamental post-cloud paradigms and propose a new method to meet the challenges using simulations methods. Finally, it concludes the paper and highlights prospects for future research.