论文标题
热纯量子矩阵产品状态恢复卷法纠缠
Thermal Pure Quantum Matrix Product States Recovering a Volume Law Entanglement
论文作者
论文摘要
我们提出了一种构建热纯量子矩阵乘积（TPQ-MP）的方法，该量子量矩阵乘积（TPQ-MP）可以模拟有限温度量子多体系统，其数值成本与基态的矩阵乘积算法相当。国会议员最初是针对带有区域法纠缠的波函数设计的。但是，通过将辅助位点连接到随机矩阵乘积状态的边缘，我们发现纠缠程度会自动调整，以恢复特征在于TPQ状态的纠缠熵的体积定律。 TPQ-MPS评估的横向ISING的有限温度物理量以及Spin-1/2 Heisenberg链显示出了极好的一致性，即使对于债券尺寸$ \ sim 10 $ -20 $ - $ 20 $，与确切的结果相关。
We propose a way to construct a thermal pure quantum matrix product state (TPQ-MPS) that can simulate finite temperature quantum many-body systems with a minimal numerical cost comparable to the matrix product algorithm for the ground state. The MPS was originally designed for the wave function with area-law entanglement. However, by attaching the auxiliary sites to the edges of the random matrix product state, we find that the degree of entanglement is automatically tuned so as to recover the volume law of the entanglement entropy that characterizes the TPQ state. The finite temperature physical quantities of the transverse Ising and the spin-1/2 Heisenberg chains evaluated by a TPQ-MPS show excellent agreement even for bond dimension $\sim 10$-$20$ with those of the exact results.
