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Prime Number Primality Testing via Quantum Lattice-Based Search

Jincheng Zhang

Published Aug 31, 2026• 0 citations
Publisher

Abstract

This paper introduces a novel quantum algorithm for efficient primality testing, aiming to surpass the limitations of classical methods through the application of lattice-based search. We detail the design of a quantum circuit that explores the prime number space, leveraging superposition and entanglement to achieve significantly reduced computational complexity. The core mechanism centers around quantum search, allowing for parallel exploration of the vast space of possible prime factors. We present a comprehensive analysis of the algorithm's performance, including a detailed mathematical justification of its efficiency gains compared to established techniques. The paper concludes with a discussion of the potential implications of this quantum approach for cryptography and other applications requiring prime number verification.

DOI
10.5281/zenodo.22188284

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This paper introduces a novel probabilistic optimization algorithm leveraging the unique capabilities of quantum computing. Traditional optimization techniques often struggle with large-scale problems, limiting their applicability. We propose a quantum-enhanced algorithm designed to accelerate and improve the solution of complex optimization tasks. This algorithm utilizes quantum mechanics principles to enhance the search process, leading to more efficient and accurate results. The core mechanism centers around quantum superposition and entanglement to explore solution spaces in a fundamentally different manner. We detail the algorithm's design, the quantum circuit implementation, and the resulting performance improvements compared to classical approaches. The paper concludes with a discussion of the potential implications of this approach for various real-world optimization challenges.
Quantum entanglement, a bizarre and fundamental property of quantum mechanics, presents a potentially revolutionary approach to computation and search. This paper explores the development of a novel quantum search algorithm predicated on entanglement, aiming to surpass the limitations of traditional methods by offering enhanced efficiency and potential for tackling complex data sets. We detail the core mechanism of this algorithm, emphasizing its reliance on the unique correlations inherent in entangled states, and present a preliminary analysis of its performance characteristics. The investigation will focus on demonstrating the algorithm's capability to efficiently locate specific data points within a large dataset, highlighting the conceptual advantages over existing search techniques. The core claim is that this quantum search algorithm achieves significantly improved performance, particularly in scenarios with high dimensionality or complex search spaces. We conclude with a discussion of potential future directions and challenges in implementing this algorithm.
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