Researchers have proposed a novel approach to unordered database search using distributed quantum algorithms, which can significantly reduce circuit depth and mitigate noise in the Noisy Intermediate-Scale Quantum (NISQ) era. By dividing the target string into substrings and constructing query operators for subfunctions, this method improves upon Grover's algorithm, achieving quadratic acceleration over classical algorithms. The proposed algorithm enables the integration of query operators for multiple substrings, allowing for more efficient search processes. This development has significant implications for quantum computing, as it can decrease the depth of quantum circuits and reduce error rates1. The ability to efficiently search large databases is crucial for various applications, including cryptography and optimization problems. So what matters to practitioners is that this advancement brings quantum computing closer to practical applications, potentially disrupting the current landscape of computation and cryptography.