Optimizing parameterized quantum circuits (PQCs) is the leading approach to make use of near-term quantum computers. However, very little is known about the cost function landscape for PQCs, which hinders progress towards quantum-aware optimizers. In this work, we investigate the connection between three different landscape features that have been observed for PQCs: (1) exponentially vanishing gradients (called barren plateaus), (2) exponential cost concentration about the mean, and (3) the exponential narrowness of minina (called narrow gorges). We analytically prove that these three phenomena occur together, i.e., when one occurs then so do the other two. A key implication of this result is that one can numerically diagnose barren plateaus via cost differences rather than via the computationally more expensive gradients. More broadly, our work shows that quantum mechanics rules out certain cost landscapes (which otherwise would be mathematically possible), and hence our results are interesting from a quantum foundations perspective.
翻译:优化参数化量子电路(PQCs)是使用近期量子计算机的主要方法。 但是,对PQC的成本功能景观知之甚少,这阻碍了量子觉优化的进展。 在这项工作中,我们调查了PQC所观察到的三种不同的地貌特征之间的联系:(1) 指数式消失梯度(所谓的贫瘠高原),(2) 平均值的指数成本浓度,以及(3) 微粒的指数性窄度(所谓的狭小峡谷) 。我们分析证明这三种现象是同时发生的,即当发生一种现象时,其他两种现象也发生。这一结果的一个关键含义是可以通过成本差异而不是通过计算成本上更昂贵的梯度从数字上诊断出不育的高原。更广泛地说,我们的工作表明,量子力学排除了某些成本景观(否则在数学上是可能的),因此我们的结果从量子基的角度是有趣的。