2D Lattice Liquid Models

A family of novel models of liquid on a 2D lattice (2D lattice liquid models) have been proposed as primitive models of soft-material membrane. As a first step, we have formulated them as single-component, single-layered, classical particle systems on a two-dimensional surface with no explicit viscosity. Among the family of the models, we have shown and constructed two stochastic models, a vicious walk model and a flow model, on an isotropic regular lattice and on the rectangular honeycomb lattice of various sizes. In both cases, the dynamics is governed by the nature of the frustration of the particle movements. By simulations, we have found the approximate functional form of the frustration probability, and peculiar anomalous diffusions in their time-averaged mean square displacements in the flow model. The relations to other existing statistical models and possible extensions of the models are also discussed.Comment: REVTeX4, 14 pages in double colomn, 12 figures; added references with some comments, typos fixe

Retrieving Top-N Weighted Spatial k-cliques

Spatial data analysis is a classic yet important topic because of its wide range of applications. Recently, as a spatial data analysis approach, a neighbor graph of a set P of spatial points has often been employed. This paper also considers a spatial neighbor graph and addresses a new problem, namely top-N weighted spatial k-clique retrieval. This problem searches for the N minimum weighted cliques consisting of k points in P, and it has important applications, such as community detection and co-location pattern mining. Recent spatial datasets have many points, and efficiently dealing with such big datasets is one of the main requirements of applications. A straightforward approach to solving our problem is to try to enumerate all k-cliques, which incurs O(nkk2) time. Since k ≥ 3, this approach cannot achieve the main requirement, so computing the result without enumerating unnecessary k-cliques is required. This paper achieves this challenging task and proposes a simple practically-efficient algorithm that returns the exact answer. We conduct experiments using two real spatial datasets consisting of million points, and the results show the efficiency of our algorithm, e.g., it can return the exact top-N result within 1 second when N ≤ 1000 and k ≤ 7.Taniguchi R., Amagata D., Hara T.. Retrieving Top-N Weighted Spatial k-cliques. Proceedings - 2022 IEEE International Conference on Big Data, Big Data 2022 , 4952 (2022); https://doi.org/10.1109/BigData55660.2022.10021071

Efficient Retrieval of Top-k Weighted Spatial Triangles

Due to the proliferation of location-based services and IoT devices, a lot of spatial points are being generated. Spatial data analysis is well known to be an important task. As spatial data analysis tools, graphs consisting of spatial points, where each point has edges to its nearby points and the weight of each edge is the distance between the corresponding points, have been receiving much attention. We focus on triangles (one of the simplest sub-graph patterns) in such graphs and address the problem of retrieving the top-k weighted spatial triangles. This problem has important real-life applications, e.g., group search, urban planning, and co-location pattern mining. However, this problem is computationally challenging, because the number of triangles in a graph is generally huge and enumerating all of them is not feasible. To solve this challenge, we propose an efficient algorithm that returns the exact result. Our experimental results on real datasets show the efficiency of our algorithm.This version of the contribution has been accepted for publication, after peer review (when applicable) but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/978-3-031-00123-9_17

Efficient Retrieval of Top-k Weighted Triangles on Static and Dynamic Spatial Data

Due to the proliferation of location-based services, spatial data analysis becomes more and more important. We consider graphs consisting of spatial points, where each point has edges to its nearby points and the weight of each edge is the distance between the corresponding points, as they have been receiving attention as spatial data analysis tools. We focus on triangles in such graphs and address the problem of retrieving the top- $k$ weighted spatial triangles. This problem is computationally challenging, because the number of triangles in a graph is generally huge and enumerating all of them is not feasible. To overcome this challenge, we propose an algorithm that returns the exact result efficiently. We moreover consider two dynamic data models: (i) fully dynamic data that allow arbitrary point insertions and deletions and (ii) streaming data in a sliding-window model. They often appear in location-based services. The results of our experiments on real datasets show the efficiency of our algorithms for static and dynamic data.Taniguchi R., Amagata D., Hara T.. Efficient Retrieval of Top-k Weighted Triangles on Static and Dynamic Spatial Data. IEEE Access 10, 55298 (2022); https://doi.org/10.1109/ACCESS.2022.3177620

Interaction induced AC-Stark shift of exciton-polaron resonances

Laser induced shift of atomic states due to the AC-Stark effect has played a central role in cold-atom physics and facilitated their emergence as analog quantum simulators. Here, we explore this phenomena in an atomically thin layer of semiconductor MoSe$_2$, which we embedded in a heterostructure enabling charge tunability. Shining an intense pump laser with a small detuning from the material resonances, we generate a large population of virtual collective excitations, and achieve a regime where interactions with this background population is the leading contribution to the AC-Stark shift. Using this technique we study how itinerant charges modify -- and dramatically enhance -- the interactions between optical excitations. In particular, our experiments show that the interaction between attractive polarons could be two orders of magnitude stronger than those between bare excitons