Experimental study on the quantum search algorithm over structured datasets using IBMQ experience

Abstract

In this work, a quantum search algorithm over structured datasets is proposed. Subsequently, the algorithm is executed on a real chip quantum computer developed by IBM Quantum experience (IBMQ). QISKit, the software platform developed by IBM, is used for the implementation of this algorithm. Quantum interference, quantum superposition, and π phase shift of the quantum state are applied in the proposed search algorithm. It performs a π phase shift on the initial state and conducts a state elimination and amplitude amplification process to reach the 'search key' or 'solution key' from the given structured dataset. The proposed quantum algorithm is executed using the QISKit SDK local backend ‘local_qasm_simulator’, real chip 'ibmq_16_melbourne', 'ibmq_belem' and 'ibmqx4′ IBMQ. The results suggest that the real chipibmq_16_melbourne is more quantum error- or noise-prone than ibmq_belem and ibmqx4. The correctness, validation, and application using the proposed algorithm are demonstrated. The algorithm is very promising in terms of low quantum cost and fewer gate requirements. This implies that the proposed quantum search algorithm may be a compelling and pertinent choice in the Noisy Intermediate-Scale Quantum (NISQ) technology era.

Keywords

• Quantum transformation
• Quantum interference
• IBM Quantum experience (IBMQ)
• Hadamard transformation
• QISKit SDK
• Noisy Intermediate-Scale Quantum (NISQ)