Towards Practical Quantum Phase Estimation: A Modular, Scalable, and Adaptive Approach

TL;DR

This paper introduces AWQPE, a modular and adaptive quantum phase estimation algorithm that reduces resource requirements and improves accuracy for near-term quantum devices by using parallelizable control qubit blocks.

Contribution

The paper presents a novel adaptive windowed QPE method that enhances efficiency and robustness, suitable for NISQ devices, by employing independent control qubit blocks and an ambiguity resolution mechanism.

Findings

AWQPE reduces the number of iterations needed for high-precision phase estimation.

The algorithm demonstrates robustness and accuracy in numerical simulations.

AWQPE is well-suited for implementation on near-term quantum hardware.

Abstract

Quantum Phase Estimation (QPE) is a cornerstone algorithm in quantum computing, with applications ranging from integer factorization to quantum chemistry simulations. However, the resource demands of standard QPE, which require a large number of coherent qubits and deep circuits, pose significant challenges for current Noisy Intermediate Scale Quantum (NISQ) devices. In this work, we introduce the Adaptive Windowed Quantum Phase Estimation (AWQPE) algorithm, a novel method designed to address the limitations of standard QPE. AWQPE utilizes small, independent blocks of $m > 1$ control qubits to estimate multiple phase bits simultaneously within a "window,'' thereby significantly reducing the number of iterations required to achieve a desired precision. These independent blocks are amenable to parallelization and, when combined with a robust least-significant-bit (LSB) to most-significant-bit (MSB) ambiguity resolution mechanism, enhance the algorithm's accuracy while mitigating the risk of error propagation. Our numerical simulations demonstrate AWQPE's accuracy and robustness, showcasing a distinct balance between resource efficiency and computational speed. This makes AWQPE particularly well-suited for near-term quantum platforms.