Escaping Barren Plateau: Co-Exploration of Quantum Circuit Parameters and Architectures

TL;DR

This paper introduces AntiBP, a co-exploration framework for quantum circuit parameters and architectures that effectively mitigates barren plateau issues in variational quantum algorithms, especially under noise.

Contribution

The paper presents a novel co-exploration framework, AntiBP, for designing quantum circuit architectures and parameters to avoid barren plateaus in VQEs.

Findings

AntiBP effectively avoids barren plateaus in noise-free environments.

AntiBP outperforms baseline VQEs in noisy environments.

The framework adapts to application-specific circuit scales.

Abstract

Barren plateaus (BP), characterized by exponentially vanishing gradients that hinder the training of variational quantum circuits (VQC), present a pervasive and critical challenge in applying variational quantum algorithms to real-world applications. It is widely recognized that the BP problem becomes more pronounced with an increase in the number of parameters. This work demonstrates that the BP problem manifests at different scales depending on the specific application, highlighting the absence of a universal VQC ansatz capable of resolving the BP issue across all applications. Consequently, there is an imminent need for an automated tool to design and optimize VQC architectures tailored to specific applications. To close the gap, this paper takes Variational Quantum Eigensolvers (VQEs) as a vehicle, and we propose a novel quantum circuit parameter and architecture co-exploration framework, namely AntiBP. Experimental results demonstrate that AntiBP effectively avoids the BP issue for circuits that are not under-parameterized in noise-free environments. Furthermore, AntiBP significantly outperforms baseline VQEs in noisy environments.