String matching is a fundamental problem in computer science, with critical applications in text retrieval, bioinformatics, and data analysis. Among the numerous solutions that have emerged for this problem in recent decades, bit-parallelism has significantly enhanced their practical efficiency, leading to the development of several optimized approaches for both exact and approximate string matching. However, their potential in quantum computing remains largely unexplored. This paper presents a novel pathway that not only translates bit-parallel string matching algorithms into the quantum framework but also enhances their performance to achieve a quadratic speedup through Grover's search. By embedding quantum search within a bit-parallel model, we reduce the time complexity of string matching, establishing a structured pathway for transforming classical algorithms into quantum solutions with provable computational advantages. Beyond exact matching, this technique offers a foundation for tackling a wide range of non-standard string matching problems, opening new avenues for efficient text searching in the quantum era. To demonstrate the simplicity and adaptability of the technique presented in this paper, we apply this translation and adaptation process to two landmark bit-parallel algorithms: Shift-And for exact pattern matching and Shift-Add for approximate string matching with up to k errors.

翻译：字符串匹配是计算机科学中的一个基础问题，在文本检索、生物信息学和数据分析中具有关键应用。近几十年来针对该问题涌现的众多解决方案中，位并行技术显著提升了实际效率，催生了多种针对精确与近似字符串匹配的优化方法。然而，其在量子计算中的潜力仍很大程度上未被探索。本文提出了一种创新路径，不仅将位并行字符串匹配算法转换至量子框架，还通过Grover搜索实现性能增强以获得二次加速。通过将量子搜索嵌入位并行模型，我们降低了字符串匹配的时间复杂度，为将经典算法转化为具有可证明计算优势的量子解决方案建立了结构化路径。除精确匹配外，该技术为解决各类非标准字符串匹配问题奠定了基础，为量子时代的高效文本搜索开辟了新途径。为展示本文所提技术的简洁性与适应性，我们将此转换与适配过程应用于两个里程碑式的位并行算法：用于精确模式匹配的Shift-And算法，以及支持最多k个错误的近似字符串匹配的Shift-Add算法。