Practical Implementation of a Quantum String Matching Algorithm

String matching stands as a cornerstone problem in computer science, finding extensive application in many fields, such as data mining, text retrieval, and bioinformatics, just to cite a few. Its essence lies in identifying all occurrences of a specified pattern, typically denoted by length m, within a text of length n. Despite its seemingly straightforward formulation, the problem has sparked a plethora of solutions, stemming from diverse computational paradigms and approaches. Classical solutions exhibit a worst-case time complexity of Θ(n), contrasting with the capability of quantum computation to achieve a [EQUATION] complexity using Grover search, thereby realizing a quadratic speed-up compared to classical methods. This article presents a first practical implementation of a quantum circuit tailored to address string matching, particularly focusing on binary strings. The exposition delves into the technical intricacies of the implementation, which leverages the Qiskit open-source toolkit developed by IBM. By elucidating various algorithmic nuances overlooked in prior theoretical formulations, our solution serves as a conduit between the realms of text processing and quantum computing, fostering cross-disciplinary dialogue and innovation. While current real-world hardware lacks the capability to execute the proposed circuit, particularly when dealing with lengthy texts, this study presents experimental results from a simulation of the circuit on classical hardware, serving to validate the efficacy of the proposed implementation.