Work

Low-depth Amplitude Estimation without Really Trying

Year: 2025

Type: article

Abstract: Standard quantum amplitude estimation algorithms provide quadratic speedup to Monte-Carlo simulations but require a circuit depth that scales as inverse of the estimation error. In view of the shallow depth in near-term devices, the precision achieved by these algorithms would be low. In this article, we bypass this limitation by performing the classical Monte-Carlo method on the quantum algorithm itself, achieving a higher than classical precision using low-depth circuits. We require the quantum algorithm to be weakly biased in order to avoid error accumulation during this process. Our method is parallel and can be as weakly biased as the constituent algorithm in some cases.

Source: ACM Transactions on Quantum Computing

DOI: 10.1145/3748666

Authors: Dinh-Long Vu, Bin Cheng, Patrick Rebentrost

Institutions: Centre for Quantum Technologies, National University of Singapore

Language: English

Topic: Quantum Computing Algorithms and Architecture

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: National Research Foundation, National Research Foundation Singapore

Award: G5428356290