2025/06/28 by Floyd M. Creevey, Mingrui Jing, Creevey, Floyd M. +3 · 1 citation
Computer Science · #FOS: Physical sciences #Quantum Computing Algorithms and Architecture #Quantum Information and Cryptography #Quantum Physics (quant-ph) #Quantum-Dot Cellular Automata
paper · pdf · doi:10.48550/arxiv.2506.22775
openalex publication_date 2025/06/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper presents the implementation of a quantum sequence alignment (QSA) algorithm on biological data in environments simulating noisy intermediate-scale quantum (NISQ) computers. The approach to quantum bioinformatics adapts the original QSA algorithm proposed in 2000 to current capabilities and limitations of NISQ-era quantum computers and uses a genetic algorithm for state preparation (GASP) to create encoding circuits to load both database and target sequences into the quantum data registers. The implementation is tested in a simulated quantum computer environment to validate the approach and refine the GASP data-loading circuit designs. The results demonstrate the practicalities of deploying the QSA algorithm and exemplify the potential of GASP for data encoding in the realm of quantum circuit design, particularly for complex algorithms in quantum bioinformatics and other data-rich problems.