Comparative Study of Variations in Quantum Approximate Optimization Algorithms for the Traveling Salesman Problem.

The traveling salesman problem (TSP) is one of the most often-used NP-hard problems in computer science to study the effectiveness of computing models and hardware platforms. In this regard, it is also heavily used as a vehicle to study the feasibility of the quantum computing paradigm for this class of problems. In this paper, we tackle the TSP using the quantum approximate optimization algorithm (QAOA) approach by formulating it as an optimization problem.

Graph formations of partial-order multiple-sequence alignments using nanoscale, microscale, and multiscale reconfigurable meshes.

In this paper, we show how to form partial-order multiple-sequence alignment graphs on two types of reconfigurable mesh architectures. The first reconfigurable mesh is a standard microscale that uses electrical interconnects, while the second type of reconfigurable mesh can be implemented at a nanoscale level and employs spin waves for interconnectivity. We consider graph formations for two cases.