A Scalable 5,6-Qubit Grover's Quantum Search Algorithm
This work addresses the problem of limited exploration of larger search spaces in quantum computing for researchers, though it appears incremental as it extends existing methods to slightly higher qubit counts.
The paper tackles the challenge of scaling Grover's quantum search algorithm to larger qubit sizes by introducing a scalable implementation for 5-qubit and 6-qubit circuits, achieving a probability of finding the correct entity in the high nineties and benchmarking it against state-of-the-art smaller implementations.
Recent studies have been spurred on by the promise of advanced quantum computing technology, which has led to the development of quantum computer simulations on classical hardware. Grover's quantum search algorithm is one of the well-known applications of quantum computing, enabling quantum computers to perform a database search (unsorted array) and quadratically outperform their classical counterparts in terms of time. Given the restricted access to database search for an oracle model (black-box), researchers have demonstrated various implementations of Grover's circuit for two to four qubits on various platforms. However, larger search spaces have not yet been explored. In this paper, a scalable Quantum Grover Search algorithm is introduced and implemented using 5-qubit and 6-qubit quantum circuits, along with a design pattern for ease of building an Oracle for a higher order of qubits. For our implementation, the probability of finding the correct entity is in the high nineties. The accuracy of the proposed 5-qubit and 6-qubit circuits is benchmarked against the state-of-the-art implementations for 3-qubit and 4-qubit. Furthermore, the reusability of the proposed quantum circuits using subroutines is also illustrated by the opportunity for large-scale implementation of quantum algorithms in the future.