Barren plateaus are amplified by the dimension of qudits
This addresses a critical obstacle for quantum computing researchers, but it is incremental as it builds on existing literature about barren plateaus.
The paper tackles the vanishing gradient problem (barren plateaus) in Variational Quantum Algorithms by showing that qudit dimensionality intrinsically amplifies this issue, with numerical results exemplifying the impact.
Variational Quantum Algorithms (VQAs) have emerged as pivotal strategies for attaining quantum advantage in diverse scientific and technological domains, notably within Quantum Neural Networks. However, despite their potential, VQAs encounter significant obstacles, chief among them being the vanishing gradient problem, commonly referred to as barren plateaus. In this article, through meticulous analysis, we demonstrate that existing literature implicitly suggests the intrinsic influence of qudit dimensionality on barren plateaus. To instantiate these findings, we present numerical results that exemplify the impact of qudit dimensionality on barren plateaus. Therefore, despite the proposition of various error mitigation techniques, our results call for further scrutiny about their efficacy in the context of VQAs with qudits.