The Algorithmic Structure of Quantum Computing

Donwoo Lee, Seungjae Lee, Sudeok Shon

Since the mention of the Fourth Industrial Revolution in 2016, quantum computers and quantum computing (QC) have emerged as key technologies. Many researchers are trying to realize quantum computers and quantum computing. In particular, most of the development and application of metaheuristics algorithms using quantum computing is focused on computer engineering fields. Cases in which the developed algorithm is applied to the optimal design of a building or the optimal design results presented by expanding the algorithm in various directions are very insufficient. Therefore, in this paper, we proposed four methods of adopting qubits to perform pitch adjusting in the optimization process of the QbHS (quantum-based harmony search) algorithm and applied it to TTO (truss topology optimization) using four methods to compare the results. The four methods of adopting qubits have the same or decreased number of qubits adopted as the number of iterations changes. As a result of applying TTO using four methods, convergence performance differed depending on the adoption method, and convergence performance was superior to conventional HS (harmony search) algorithms in all methods. The optimal design of structural engineering using such QC is expected to contribute to the revitalization of future technologies in the architectural field and the field of computer information systems.

Jincheng Zhang

This paper investigates the application of nonlinear topological topology structures within quantum algorithm computation, aiming to enhance efficiency and stability. We explore a novel quantum algorithm design framework predicated on these structures, presenting a potential pathway towards improved quantum computation. The core claim is that leveraging these topological properties can significantly accelerate and stabilize quantum computations. This work introduces a framework that utilizes the inherent properties of topological structures to optimize quantum algorithm design.

Shinil Cho

Jincheng Zhang

This paper presents a novel quantum computation algorithm based on graph theory, aiming to simplify quantum computations by leveraging graph structure characteristics. Traditional quantum computing often struggles with efficiently utilizing graph structures, leading to complex algorithms. Our approach transforms the core quantum computation process into a graph representation, employing graph nodes and edges to design an optimized quantum computation. The core mechanism focuses on reducing computational complexity through the intelligent design of the graph structure itself. This paper details the algorithm's architecture, the rationale behind the graph representation, and the resulting efficiency gains compared to traditional methods. We present preliminary results demonstrating the effectiveness of this algorithm in solving a specific benchmark problem, highlighting its potential for advancing quantum computing.

Craig S. Lent