A large amount of effort has recently been put into understanding the barren
plateau phenomenon. In this perspective article, we face the increasingly loud
elephant in the room and ask a question that has been hinted at by many but not
explicitly addressed: Can the structure that allows one to avoid barren
plateaus also be leveraged to efficiently simulate the loss classically? We
present strong evidence that commonly used models with provable absence of
barren plateaus are also classically simulable, provided that one can collect
some classical data from quantum devices during an initial data acquisition
phase. This follows from the observation that barren plateaus result from a
curse of dimensionality, and that current approaches for solving them end up
encoding the problem into some small, classically simulable, subspaces. This
sheds serious doubt on the non-classicality of the information processing
capabilities of parametrized quantum circuits for barren plateau-free
landscapes and on the possibility of superpolynomial advantages from running
them on quantum hardware. We end by discussing caveats in our arguments, the
role of smart initializations, and by highlighting new opportunities that our
perspective raises.

基于对贫瘠高原现象的理解，本文探讨了一个引人注目的问题：利用允许避免贫瘠高原的结构是否也可以用于在经典上高效模拟损失，通过在初步数据获取阶段从量子设备中收集一些经典数据，我们表明常用的具有可证明无贫瘠高原的模型也可以在经典上模拟，这对于参数化量子电路的非经典信息处理能力以及在量子硬件上运行的超多项式优势的可能性提出了严重质疑，最后讨论了我们观点中的警示性因素、智能初始化的作用，并强调了新的机遇。