Deterministic Dense Coding and Faithful Teleportation with Multipartite Graph States

We proposed novel schemes to perform the deterministic dense coding and faithful teleportation with multipartite graph states. We also find the sufficient and necessary condition of a viable graph state for the proposed scheme. That is, for the associated graph, the reduced adjacency matrix of the Tanner-type subgraph between senders and receivers should be invertible.Comment: 10 pages, 1 figure;v2. discussions improve

Multipartite Entanglement Measures and Quantum Criticality from Matrix and Tensor Product States

We compute the multipartite entanglement measures such as the global entanglement of various one- and two-dimensional quantum systems to probe the quantum criticality based on the matrix and tensor product states (MPSs/TPSs). We use infinite time-evolving block decimation (iTEBD) method to find the ground states numerically in the form of MPSs/TPSs, and then evaluate their entanglement measures by the method of tensor renormalization group (TRG). We find these entanglement measures can characterize the quantum phase transitions by their derivative discontinuity right at the critical points in all models considered here. We also comment on the scaling behaviors of the entanglement measures by the ideas of quantum state renormalization group transformations.Comment: 22 pages, 11 figure

Intramuscular Hemangioma of the Temporalis Muscle With Incidental Finding of Bilateral Symmetric Calcification of the Basal Ganglia: A Case Report

We report an 11-year-old boy whose brain computed tomography findings incidentally revealed bilateral basal ganglia calcification. He was symptom-free and had no abnormal neurological findings. He was diagnosed with Fahr's disease based on radiological findings and after excluding other etiologies such as infection, metabolic disorders, congenital malformation and malignancies. Most of the reported cases display an autosomal dominant mode of inheritance. Although Fahr's disease is a rare cause of basal ganglia calcification in children, this disease should be considered in children with a family history of neuropsychiatric disorders

Quantum Annealing Approach for the Optimal Real-time Traffic Control using QUBO

Traffic congestion is one of the major issues in urban areas, particularly when traffic loads exceed the roads capacity, resulting in higher petrol consumption and carbon emissions as well as delays and stress for road users. In Asia, the traffic situation can be further deteriorated by road sharing of scooters. How to control the traffic flow to mitigate the congestion has been one of the central issues in transportation research. In this study, we employ a quantum annealing approach to optimize the traffic signals control at a real-life intersection with mixed traffic flows of vehicles and scooters. Considering traffic flow is a continuous and emerging phenomenon, we used quadratic unconstrained binary optimization (QUBO) formalism for traffic optimization, which has a natural equivalence to the Ising model and can be solved efficiently on the quantum annealers, quantum computers or digital annealers. In this article, we first applied the QUBO traffic optimization to artificially generated traffic for a simple intersection, and then we used real-time traffic data to simulate a real Dongda-Keyuan intersection with dedicated cars and scooter lanes, as well as mixed scooter and car lanes. We introduced two types of traffic light control systems for traffic optimization C-QUBO and QUBO. Our rigorous QUBO optimizations show that C-QUBO and QUBO outperform the commonly used fixed cycle method, with QUBO outperforming C-QUBO in some instances. It has been found that QUBO optimization significantly relieves traffic congestion for the unbalanced traffic volume. Furthermore, we found that dynamic changes in traffic light signal duration greatly reduce traffic congestion.Comment: 2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), 24-26 November 202