This paper presents a quantum mechanical algorithm for database search that is significantly faster than any classical algorithm. The problem involves searching for a single item in an unsorted database of N items, where each item can be checked in one step to determine if it satisfies a given condition. Classically, this would require an average of N/2 steps. However, using quantum mechanics, the algorithm can find the desired item in O(√N) steps, which is optimal. The algorithm works by creating a superposition of all possible states, applying a transformation that amplifies the amplitude of the desired state, and then measuring the result. The key steps involve the creation of a uniform superposition, the application of a diffusion transform (inversion about average), and a conditional phase shift. The diffusion transform is shown to be equivalent to an inversion about average operation, which increases the amplitude of the desired state. The algorithm is proven to be optimal, as it matches the lower bound of Ω(√N) steps required to identify the desired item. The paper also discusses the implementation of the algorithm, noting that it is simpler than other quantum algorithms due to the use of the Walsh-Hadamard transform and conditional phase shift operations. Additionally, the algorithm can be adapted to handle multiple items satisfying the condition and can be combined with other quantum algorithms to design faster search methods. The paper concludes with references to related works and acknowledges the contributions of others in the field of quantum computing.This paper presents a quantum mechanical algorithm for database search that is significantly faster than any classical algorithm. The problem involves searching for a single item in an unsorted database of N items, where each item can be checked in one step to determine if it satisfies a given condition. Classically, this would require an average of N/2 steps. However, using quantum mechanics, the algorithm can find the desired item in O(√N) steps, which is optimal. The algorithm works by creating a superposition of all possible states, applying a transformation that amplifies the amplitude of the desired state, and then measuring the result. The key steps involve the creation of a uniform superposition, the application of a diffusion transform (inversion about average), and a conditional phase shift. The diffusion transform is shown to be equivalent to an inversion about average operation, which increases the amplitude of the desired state. The algorithm is proven to be optimal, as it matches the lower bound of Ω(√N) steps required to identify the desired item. The paper also discusses the implementation of the algorithm, noting that it is simpler than other quantum algorithms due to the use of the Walsh-Hadamard transform and conditional phase shift operations. Additionally, the algorithm can be adapted to handle multiple items satisfying the condition and can be combined with other quantum algorithms to design faster search methods. The paper concludes with references to related works and acknowledges the contributions of others in the field of quantum computing.