Detection of the large scale alignment of massive galaxies at z~0.6

We report on the detection of the alignment between galaxies and large-scale structure at z~0.6 based on the CMASS galaxy sample from the Baryon Oscillation Spectroscopy Survey data release 9. We use two statistics to quantify the alignment signal: 1) the alignment two-point correlation function which probes the dependence of galaxy clustering at a given separation in redshift space on the projected angle (theta_p) between the orientation of galaxies and the line connecting to other galaxies, and 2) the cos(2theta)-statistic which estimates the average of cos(2theta_p) for all correlated pairs at given separation. We find significant alignment signal out to about 70 Mpc/h in both statistics. Applications of the same statistics to dark matter halos of mass above 10^12 M_sun/h in a large cosmological simulation show similar scale-dependent alignment signals to the observation, but with higher amplitudes at all scales probed. We show that this discrepancy may be partially explained by a misalignment angle between central galaxies and their host halos, though detailed modeling is needed in order to better understand the link between the orientations of galaxies and host halos. In addition, we find systematic trends of the alignment statistics with the stellar mass of the CMASS galaxies, in the sense that more massive galaxies are more strongly aligned with the large-scale structure.Comment: 6 pages, 3 figures, accepted for publication in ApJ Letter

Different contributions to space weather and space climate from different big solar active regions

The purpose of this paper is to show that large active regions (ARs) with different magnetic configurations have different contributions to short-term and long-term variations of the Sun. As a case study, the complex $\delta$-type AR 12673 and the simple $\beta$-type AR 12674 are investigated in detail. Since the axial dipole moment at cycle minimum determines the amplitude of the subsequent cycle and space climate, we have assimilated the individual observed magnetic configurations of these two ARs into a surface flux transport model to compare their contributions to the axial dipole moment $D$. We find that AR 12673 has a significant effect on $D$ at the end of the cycle, making it weaker because of the abnormal and complicated magnetic polarities. An initial strongly positive $D$ ends up with a strongly negative value. The flare-poor AR 12674 has a greater contribution to the long-term axial dipole moment than the flare-rich AR 12673. We then carry out a statistical analysis of ARs larger than 800 $\mu$Hem from 1976 to 2017. We use the flare index FI and define an axial dipole moment index DI to quantify the effects of each AR on space weather and space climate, respectively. Whereas the FI has a strong dependence on the magnetic configuration, the DI shows no such dependence. The DI is mainly determined by the latitudinal location and the latitudinal separation of the positive and negative magnetic fluxes of the ARs. Simple ARs have the same possibility as complex ARs to produce big DI values affecting space climate.Comment: 18 pages, 8 figures, Accepted for publication in the Astrophysical Journa

Research on the Development Status and the Trend of Smart Home

The emergence of the Internet of Things (IoT) technology provides new directions and contents for the development of smart homes, breaks the time and space barriers between people and home systems, and the application of IoT technology realizes the integration and management of information between smart home devices, prompting people\u27s home life to be safe, comfortable and intelligent, exploring the life needs of contemporary users, and building a harmonious relationship between people and smart home systems. At present, smart home is developing rapidly and has a greater impact on people\u27s home life. This paper will elaborate on the development status of smart homes in the context of the Internet of Things and explore and study the significance and development trend of Internet of Things technology in the field of the smart home

Coordinated Multi-Agent Patrolling with History-Dependent Cost Rates -- Asymptotically Optimal Policies for Large-Scale Systems

We study a large-scale patrol problem with history-dependent costs and multi-agent coordination, where we relax the assumptions on the past patrol studies, such as identical agents, submodular reward functions and capabilities of exploring any location at any time. Given the complexity and uncertainty of the practical situations for patrolling, we model the problem as a discrete-time Markov decision process (MDP) that consists of a large number of parallel restless bandit processes and aim to minimize the cumulative patrolling cost over a finite time horizon. The problem exhibits an excessively large size of state space, which increases exponentially in the number of agents and the size of geographical region for patrolling. We extend the Whittle relaxation and Lagrangian dynamic programming (DP) techniques to the patrolling case, where the additional, non-trivial constraints used to track the trajectories of all the agents are inevitable and significantly complicate the analysis. The past results cannot ensure the existence of patrol policies with theoretically bounded performance degradation. We propose a patrol policy applicable and scalable to the above mentioned large, complex problem. By invoking Freidlin's theorem, we prove that the performance deviation between the proposed policy and optimality diminishes exponentially in the problem size.Comment: 37 pages, 4 figure