论文标题
有效构建多体高斯州的张量网络表示
Efficient construction of tensor-network representations of many-body Gaussian states
论文作者
论文摘要
我们提出了一个程序，可以有效地构建多体高斯状态的张量 - 网络表示表示。这些状态包括骨髓和费米的二次汉密尔顿人的地面和热状态，这对于研究量子多体系统至关重要。该过程将构建多体高斯状态的计算时间要求提高了五个数量级，以使合理的参数值，从而使模拟超出了迄今为止可行的范围。我们的过程结合了高斯量子信息理论的思想与基于张量的数值方法的想法，从而在张量 - 网络模拟中开放了利用高斯方法的丰富工具吉他的可能性。
We present a procedure to construct tensor-network representations of many-body Gaussian states efficiently and with a controllable error. These states include the ground and thermal states of bosonic and fermionic quadratic Hamiltonians, which are essential in the study of quantum many-body systems. The procedure improves computational time requirements for constructing many-body Gaussian states by up to five orders of magnitude for reasonable parameter values, thus allowing simulations beyond the range of what was hitherto feasible. Our procedure combines ideas from the theory of Gaussian quantum information with tensor-network based numerical methods thereby opening the possibility of exploiting the rich tool-kit of Gaussian methods in tensor-network simulations.
