AI 中文总结
评论针对一篇研究数值方法和量子处理器模拟量子退火协议适用性的文章，重新审视神经量子态精度问题，证明考虑蒙特卡洛噪声等因素时，神经量子态在某些情况能提供有竞争力结果。
AI 中文摘要
最近一篇文章研究了数值方法和量子处理器单元在模拟量子退火协议中的适用性。其中一项发现表明，基于人工神经网络的多体波函数通用变分假设——神经量子态，无法达到与量子处理器相同的精度。在本评论中，我们重新审视了这些问题，证明在考虑蒙特卡洛噪声和最终状态样本之间的大自相关时间时，神经量子态在某些情况下可以提供有竞争力的结果。
英文摘要
A recent article [Science 388, 199-204 (2025)] investigates the applicability of numerical methods and a quantum processor unit in simulating a quantum annealing protocol. One of the findings indicates that Neural Quantum States - a versatile variational ansatz for the many-body wave function based on artificial neural networks - fail to reach the same accuracy as the quantum processor. In this comment we revisit these concerns, demonstrating that NQS can provide competitive results in some of the cases when accounting for the Monte-Carlo noise and large autocorrelation times between samples obtained from the final state.
Comments3 pages, 1 figure; Comment on arXiv:2403.00910v2
