Dimension Reduction Quantum Computing (VQC) Optimization Algorithm

Jincheng Zhang

Published Sep 2, 2026• 0 citations

Abstract

This paper introduces a novel optimization algorithm, termed Dimension Reduction Quantum Computing (VQC), designed to enhance the utilization of quantum resources in quantum computing. Traditional quantum algorithms often struggle with the limitations of a fixed qubit state space, leading to suboptimal resource allocation and computational inefficiency. VQC leverages the principles of quantum entanglement to dynamically adjust qubit parameters, effectively reducing the dimensionality of the quantum state space. This reduction in dimensionality unlocks new computational pathways and improves the speed and efficiency of quantum computations. The core mechanism focuses on leveraging entanglement to represent and manipulate quantum states, promoting a more efficient utilization of available qubits. The proposed algorithm demonstrates significant improvements in several benchmark quantum algorithms, highlighting its potential to revolutionize quantum computing by maximizing resource utilization and accelerating computational progress. The paper concludes with a detailed analysis of the algorithm's design, performance evaluation, and future research directions.

DOI: 10.5281/zenodo.22249582

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