基于自适应的量子隐形计算策略

Jincheng Zhang

Published Aug 29, 2026• 0 citations

Abstract

Quantum computing holds immense promise for revolutionizing various fields, including cryptography and drug discovery. However, the current state of quantum computing is limited by the fragility of qubits, necessitating sophisticated error correction techniques. This paper introduces a novel approach to quantum computation, termed "Adaptive Quantum Hidden Computation" (AQHC), that leverages the inherent adaptability of quantum states to enhance the efficiency and security of hidden computation. We propose a dynamic optimization algorithm that adjusts the parameters of a hidden computation based on observed error patterns, resulting in improved performance and resilience. This research emphasizes the utilization of quantum state self-adaptation to address the challenges inherent in implementing quantum algorithms. We demonstrate the efficacy of AQHC through a series of simulations and preliminary analysis, showcasing enhanced error mitigation and improved computational throughput compared to static approaches. This work represents a significant step toward creating robust and adaptable quantum computing systems.

DOI: 10.5281/zenodo.22156935

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