Classical post-processing approach for quantum amplitude estimation

TL;DR

This paper introduces a hybrid quantum-classical approach for amplitude estimation that reduces quantum resource requirements by replacing complex quantum operations with classical post-processing, enhancing practicality and efficiency.

Contribution

The paper presents a novel hybrid method for quantum amplitude estimation that minimizes quantum resource use by leveraging classical post-processing, unlike traditional quantum phase estimation techniques.

Findings

Reduces quantum gate and qubit requirements

Maintains estimation accuracy through classical post-processing

Validated by numerical simulations showing improved efficiency

Abstract

We propose an approach for quantum amplitude estimation (QAE) designed to enhance computational efficiency while minimizing the reliance on quantum resources. Our method leverages quantum computers to generate a sequence of signals, from which the quantum amplitude is inferred through classical post-processing techniques. Unlike traditional methods that use quantum phase estimation (QPE), which requires numerous controlled unitary operations and the quantum Fourier transform, our method avoids these complex and resource-demanding steps. By integrating quantum computing with classical post-processing techniques, our method significantly reduces the need for quantum gates and qubits, thus optimizing the utilization of quantum hardware. We present numerical simulations to validate the effectiveness of our method and provide a comprehensive analysis of its computational complexity and error. This hybrid strategy not only improves the practicality of QAE but also broadens its applicability in quantum computing.