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Yu-Xuan Lin

Publications and source records attributed to Yu-Xuan Lin.

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Dyonic Black Holes in Lorentz-Violating Gravity with a Background Kalb--Ramond Field

By introducing a nonminimal coupling between the Kalb--Ramond field and the electromagnetic field, we construct an exact four-dimensional static, spherically symmetric dyonic black hole solution in Lorentz-violating gravity with a background Kalb--Ramond field. The curvature invariants show that the spacetime retains a genuine curvature singularity at $r=0$. We then analyze the geodesic motion of null and timelike particles and obtain the photon-sphere radius, the shadow radius, and the innermost stable circular orbit, demonstrating that both the Lorentz-violating parameter and the dyonic charges can appreciably modify the shadow size and the domain of stable circular motion. In the extended phase space, we derive the thermodynamic quantities and verify the first law of black hole thermodynamics together with the Smarr relation. The system also exhibits a first-order phase transition between small and large black holes, and its phase structure is strongly influenced by the Lorentz-violating parameter and the dyonic charges.

gr-qc

Multi-Objective Routing Optimization Using Coherent Ising Machine in Wireless Multihop Networks

Multi-objective combinatorial optimization in wireless communication networks is a challenging task, particularly for large-scale and diverse topologies. Recent advances in quantum computing offer promising solutions for such problems. Coherent Ising Machines (CIM), a quantum-inspired algorithm, leverages the quantum properties of coherent light, enabling faster convergence to the ground state. This paper applies CIM to multi-objective routing optimization in wireless multi-hop networks. We formulate the routing problem as a Quadratic Unconstrained Binary Optimization (QUBO) problem and map it onto an Ising model, allowing CIM to solve it. CIM demonstrates strong scalability across diverse network topologies without requiring topology-specific adjustments, overcoming the limitations of traditional quantum algorithms like Quantum Approximate Optimization Algorithm (QAOA) and Variational Quantum Eigensolver (VQE). Our results show that CIM provides feasible and near-optimal solutions for networks containing hundreds of nodes and thousands of edges. Additionally, a complexity analysis highlights CIM's increasing efficiency as network size grows

quant-ph