Quantum Algorithm Compilation and Optimization

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

This paper addresses the critical challenge of quantum algorithm compilation and optimization. The core claim is to design an efficient algorithm for translating high-level algorithms into quantum circuits and subsequently optimizing them to minimize quantum resource consumption. This is achieved through a novel mechanism employing a hybrid approach combining quantum annealing and genetic algorithms to discover optimal quantum circuit implementations. The methodology focuses on reducing the number of qubits and gate operations, key factors in the feasibility of quantum computation. The presented framework offers a potential solution to the complexities inherent in mapping classical algorithms onto quantum hardware, contributing to the advancement of practical quantum computing. The paper outlines the theoretical underpinnings, the proposed optimization strategy, and discusses potential future research directions.

DOI: 10.5281/zenodo.22440410

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