We propose an optimized cluster density matrix embedding theory (CDMET). It reduces the computational cost of CDMET with simpler bath states. And the result is as accurate as the original one. As a demonstration, we study the distant correlations of the Heisenberg J ₁–J ₂ model on the square lattice. We find that the intermediate phase (0.43 ≲ J ₂ ≲ 0.62) is divided into two parts. One part is a near-critical region (0.43 ≲ J ₂ ≲ 0.50). The other part is the plaquette valence bond solid (PVB) state (0.51 ≲ J ₂ ≲ 0.62). The spin correlations decay exponentially as a function of distance in the PVB.

中文翻译：

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一种优化的簇密度矩阵嵌入理论

我们提出了一种优化的簇密度矩阵嵌入理论（CDMET）。它通过更简单的浴状态降低了 CDMET 的计算成本。结果与原始结果一样准确。作为演示，我们研究了海森堡J ₁ – J ₂模型在方格上的远距离相关性。我们发现中间相 (0.43 ≲ J ₂ ≲ 0.62) 分为两部分。一部分是近临界区 (0.43 ≲ J ₂ ≲ 0.50)。另一部分是 Plasette 价键固体 (PVB) 状态 (0.51 ≲ J ₂ ≲ 0.62)。自旋相关性作为 PVB 中距离的函数呈指数衰减。