论文标题
量子变量电路优化技术的经验评论
An Empirical Review of Optimization Techniques for Quantum Variational Circuits
论文作者
论文摘要
量子变量电路（QVC）通常被认为是近期和长期量子硬件的最有效用途之一。优化这些电路的标准方法依赖于经典系统来在每个优化步骤中计算新参数。但是，由于在所有可预见的量子硬件中逐步扩展复杂的希尔伯特空间，贫瘠的高原和噪音，因此这一过程可能极具挑战性。尽管在实践中采用了多种优化算法，但通常缺乏这种选择的理论或经验动机。为此，我们从经验上评估了许多常见梯度和无梯度优化器在各种优化任务上的潜力。这些任务包括基于经典数据和量子数据的优化例程。我们的评估是在无噪声和嘈杂的模拟中进行的。评估的大量问题和优化器为当前缺乏的QVC选择优化者提供了强有力的经验指南。
Quantum Variational Circuits (QVCs) are often claimed as one of the most potent uses of both near term and long term quantum hardware. The standard approaches to optimizing these circuits rely on a classical system to compute the new parameters at every optimization step. However, this process can be extremely challenging, due to the nature of navigating the exponentially scaling complex Hilbert space, barren plateaus, and the noise present in all foreseeable quantum hardware. Although a variety of optimization algorithms are employed in practice, there is often a lack of theoretical or empirical motivations for this choice. To this end we empirically evaluate the potential of many common gradient and gradient free optimizers on a variety of optimization tasks. These tasks include both classical and quantum data based optimization routines. Our evaluations were conducted in both noise free and noisy simulations. The large number of problems and optimizers evaluated yields strong empirical guidance for choosing optimizers for QVCs that is currently lacking.
