Modifying quantum Grover’s algorithm for dynamic multi-pattern search on reconfigurable hardware

Grover’s quantum search algorithm is a highly studied quantum algorithm that has potential applications in unstructured data search, achieving quadratic speedup over existing classical search algorithms. In this work, we propose a modified quantum circuit for multi-pattern quantum Grover’s search algorithm. Our proposed modification simplifies the conventional Grover’s algorithm circuit and makes it capable of processing dynamically changing input patterns. The proposed techniques are demonstrated using reconfigurable hardware architectures that are designed for cost-effective, scalable, high-precision and high-throughput emulation of quantum algorithms. We experimentally evaluate the modified algorithm using Field Programmable Gate Array (FPGA) hardware and provide analysis of experimental results in terms of hardware resource utilization and emulation time. Our results demonstrate successful emulation of multi-pattern Grover’s algorithm using up to 22 quantum bits on a single FPGA, which is the highest and most efficient among existing work. Hardware implementations were performed for up to 32 qubits, and emulation time results of up to 32 qubits were projected using a performance estimation model.