Iterative Qubits Management for Quantum Index Searching in a Hybrid System

TL;DR

This paper introduces IQuCS, a hybrid quantum-classical system that iteratively manages qubits for quantum index searching, significantly reducing qubit requirements and enabling more practical deployment on noisy intermediate-scale quantum hardware.

Contribution

It proposes a novel iterative qubit management method for quantum index searching that reduces qubit consumption by up to 66.2%, improving practicality on current quantum devices.

Findings

Reduces qubits consumption by up to 66.2%.

Effectively filters out unlikely data points iteratively.

Demonstrates practical implementation with Qiskit.

Abstract

Recent advances in quantum computing systems attract tremendous attention. Commercial companies, such as IBM, Amazon, and IonQ, have started to provide access to noisy intermediate-scale quantum computers. Researchers and entrepreneurs attempt to deploy their applications that aim to achieve a quantum speedup. Grover's algorithm and quantum phase estimation are the foundations of many applications with the potential for such a speedup. While these algorithms, in theory, obtain marvelous performance, deploying them on existing quantum devices is a challenging task. For example, quantum phase estimation requires extra qubits and a large number of controlled operations, which are impractical due to low-qubit and noisy hardware. To fully utilize the limited onboard qubits, we propose IQuCS, which aims at index searching and counting in a quantum-classical hybrid system. IQuCS is based on Grover's algorithm. From the problem size perspective, it analyzes results and tries to filter out unlikely data points iteratively. A reduced data set is fed to the quantum computer in the next iteration. With a reduction in the problem size, IQuCS requires fewer qubits iteratively, which provides the potential for a shared computing environment. We implement IQuCS with Qiskit and conduct intensive experiments. The results demonstrate that it reduces qubits consumption by up to 66.2%.