Resonant sequential scattering in two-frequency-pumping superradiance from a Bose-Einstein condensate

We study sequential scattering in superradiance from a Bose-Einstein condensate pumped by a two-frequency laser beam. We find that the distribution of atomic side modes presents highly different patterns for various frequency difference between the two pump components. A novel distribution is observed, with a frequency difference of eight times the recoil frequency. These observations reveal that the frequency overlap between the end-fire modes related to different side modes plays an essential role in the dynamics of sequential superradiant scattering. The numerical results from a semiclassical model qualitatively agree with our observations.Comment: Submitted to PR

When States\u27 Legislation and Constitutions Collide with Angry Locals: Shale Oil and Gas Development and Its Many Masters

This Article explores the nationally common problem of tension and conflict among state oil and gas statutes, constitutional home rule, and local control by considering intersections and tensions among the Ohio Constitution’s home rule authority, the Ohio oil and gas law’s preemption provision, and the many regulatory efforts of Ohio’s local governments. It explores the scope of the Ohio Constitution’s home rule authority, in part, by evaluating courts’ statements on the validity of several types of local ordinances, as they confront home rule and a legislative attempt at preemption. Types of local ordinances evaluated include those that prohibit or ban drilling, those that impose additional permitting fees, hearings or other requirements upon drillers, and those that pertain to more traditional exercises of zoning authority. The Article also considers some similar local control efforts in the region—in particular, in New York and Pennsylvania—which have constitutional home rule provisions similar to Ohio’s, and where, like Ohio, the shale oil and gas industry is active. By considering the constitutions, legislation, and local control efforts of nearby states that are, like Ohio, within the Utica, Marcellus, and Barnett shale plays, this Article gauges the legal circumstances under which localities might regulate the actions of the shale oil and gas industry within their borders, and under what circumstances these efforts might succeed. Because this problem presents itself throughout the country, this Article looks briefly at similar circumstances in other regions, in particular, Colorado and Texas. These states have active shale oil and gas industries, legislatures vigorously working to preempt local control, and some engaged local communities hoping to exert some influence over oil and gas activities in their jurisdictions

The Research of Car-Following Model Based on Real-Time Maximum Deceleration

This paper is concerned with the effect of real-time maximum deceleration in car-following. The real-time maximum acceleration is estimated with vehicle dynamics. It is known that an intelligent driver model (IDM) can control adaptive cruise control (ACC) well. The disadvantages of IDM at high and constant speed are analyzed. A new car-following model which is applied to ACC is established accordingly to modify the desired minimum gap and structure of the IDM. We simulated the new car-following model and IDM under two different kinds of road conditions. In the first, the vehicles drive on a single road, taking dry asphalt road as the example in this paper. In the second, vehicles drive onto a different road, and this paper analyzed the situation in which vehicles drive from a dry asphalt road onto an icy road. From the simulation, we found that the new car-following model can not only ensure driving security and comfort but also control the steady driving of the vehicle with a smaller time headway than IDM

Dependency Relationships-Enhanced Attentive Group Recommendation in HINs

Recommending suitable items to a group of users, commonly referred to as the group recommendation task, is becoming increasingly urgent with the development of group activities. The challenges within the group recommendation task involve aggregating the individual preferences of group members as the group's preferences and facing serious sparsity problems due to the lack of user/group-item interactions. To solve these problems, we propose a novel approach called Dependency Relationships-Enhanced Attentive Group Recommendation (DREAGR) for the recommendation task of occasional groups. Specifically, we introduce the dependency relationship between items as side information to enhance the user/group-item interaction and alleviate the interaction sparsity problem. Then, we propose a Path-Aware Attention Embedding (PAAE) method to model users' preferences on different types of paths. Next, we design a gated fusion mechanism to fuse users' preferences into their comprehensive preferences. Finally, we develop an attention aggregator that aggregates users' preferences as the group's preferences for the group recommendation task. We conducted experiments on two datasets to demonstrate the superiority of DREAGR by comparing it with state-of-the-art group recommender models. The experimental results show that DREAGR outperforms other models, especially HR@N and NDCG@N (N=5, 10), where DREAGR has improved in the range of 3.64% to 7.01% and 2.57% to 3.39% on both datasets, respectively.Comment: 14 pages, 9 figures, This paper has been submitted to IEEE Transactions on Knowledge and Data Engineerin