研究人员开发了一种新颖的基于Transformer的方法来对二维自旋系统进行采样，解决了Transformer在该领域常见的效率低下问题。他们的方法在每一步生成一组自旋，并利用近似概率来提高效率。该技术可以对更大的系统进行采样，例如 $180 imes 180$ 的Ising模型，并且与以前最先进的神经网络采样器相比，显示出更大的有效样本量。 AI
影响 引入了一种更有效的基于Transformer的方法来模拟复杂的物理系统，可能对科学研究产生影响。
排序理由 学术论文，详细介绍了使用Transformer对自旋系统进行采样的新方法。
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arXiv:2604.27738v1 Announce Type: cross Abstract: Autoregressive Neural Networks based on dense or convolutional layers have recently been shown to be a viable strategy for generating classical spin systems. Unlike these methods, sampling with transformers is commonly considered …
Autoregressive Neural Networks based on dense or convolutional layers have recently been shown to be a viable strategy for generating classical spin systems. Unlike these methods, sampling with transformers is commonly considered to be computationally inefficient. In this work, w…