Quantum cache memory: a framework for enhancing DNA analysis through quantum computing

Abstract

This research explores the application of quantum computing to DNA analysis, focusing on transitioning classical data to quantum information formats. We developed the Quantum Cache Memory (QCM) framework, which utilizes superposition and hybrid encoding via entanglement. The QCM framework is designed to preserve the integrity of genetic sequences throughout the quantum computing process. The effectiveness of this approach is demonstrated through implementations of single nucleotide polymorphism (SNP) detection and pattern search algorithms using a perfect quantum simulator. The results demonstrate the potential for leveraging quantum phenomena to process classical data in parallel on quantum hardware. However, the limitations of current quantum hardware and data encoding efficiency are acknowledged. This study shows the groundwork for future improvements in quantum computing ecosystems, such as the need for persistent quantum states and more effective handling of large-scale data. Our research has been conducted solely through simulations and mathematical modeling, indicating the necessity for future work on actual quantum servers.