论文标题
统一张量 - 网络电路的优化方案
Optimization schemes for unitary tensor-network circuit
论文作者
论文摘要
我们讨论具有不同网络结构的统一张量网络电路的变分优化。 ANSATZ是基于发达的多尺度纠缠重新归一化算法的概括以及具有有效的线路搜索的共轭梯度方法的。我们通过研究强烈无序的磁场和张量 - 网络$ QR $组成的heisenberg模型来介绍不同网络结构的基准计算。
We discuss the variational optimization of a unitary tensor-network circuit with different network structures. The ansatz is performed based on a generalization of well-developed multi-scale entanglement renormalization algorithm and also the conjugate-gradient method with an effective line search. We present the benchmarking calculations for different network structures by studying the Heisenberg model in a strongly disordered magnetic field and a tensor-network $QR$-decomposition.
