The Dilemma of Random Parameter Initialization and Barren Plateaus in Variational Quantum Algorithms

This paper presents an easy-to-implement approach to mitigate the challenges posed by barren plateaus (BPs) in randomly initialized parameterized quantum circuits (PQCs) within variational quantum algorithms (VQAs). Recent state-of-the-art research is flooded with a plethora of specialized strategies to overcome BPs, however, our rigorous analysis reveals that these challenging and resource heavy techniques to tackle BPs may not be required. Instead, a careful selection of distribution range to initialize the parameters of PQCs can effectively address this issue without complex modifications. We systematically investigate how different ranges of randomly generated parameters influence the occurrence of BPs in VQAs, providing a straightforward yet effective strategy to significantly mitigate BPs and eventually improve the efficiency and feasibility of VQAs. This method simplifies the implementation process and considerably reduces the computational overhead associated with more complex initialization schemes. Our comprehensive empirical validation demonstrates the viability of this approach, highlighting its potential to make VQAs more accessible and practical for a broader range of quantum computing applications. Additionally, our work provides a clear path forward for quantum algorithm developers seeking to mitigate BPs and unlock the full potential of VQAs.