论文标题
连续矩阵产品状态的各种优化
Variational optimization of continuous matrix product states
论文作者
论文摘要
正如矩阵量态忠实地代表一维量子自旋系统的基态一样,连续矩阵乘积状态(CMP)在一个空间维度中提供了相互作用场理论真空真空的忠实表示。然而,与量子自旋情况不同,密度矩阵重新归一化组和相关矩阵乘积状态算法提供了可靠的算法来优化变分状态,因此对具有不均匀外部电势的系统的CMP优化是有问题的。我们通过构建基础矩阵值函数的分段线性参数化来解决此问题,该函数可以通过高阶泰勒扩展来计算系统中各地的精确降低密度矩阵。这将变分的CMP问题变成了一种变异算法,可以从中可以精确地计算出能量及其后导数,并以缩放为键尺寸的立方体的成本计算。我们通过在外部电势中找到相互作用的玻色子的基态,以及计算连续边界条件的连续多体系统的边界或CASIMIR能量校正来说明这一点。
Just as matrix product states represent ground states of one-dimensional quantum spin systems faithfully, continuous matrix product states (cMPS) provide faithful representations of the vacuum of interacting field theories in one spatial dimension. Unlike the quantum spin case however, for which the density matrix renormalization group and related matrix product state algorithms provide robust algorithms for optimizing the variational states, the optimization of cMPS for systems with inhomogeneous external potentials has been problematic. We resolve this problem by constructing a piecewise linear parameterization of the underlying matrix-valued functions, which enables the calculation of the exact reduced density matrices everywhere in the system by high-order Taylor expansions. This turns the variational cMPS problem into a variational algorithm from which both the energy and its backwards derivative can be calculated exactly and at a cost that scales as the cube of the bond dimension. We illustrate this by finding ground states of interacting bosons in external potentials, and by calculating boundary or Casimir energy corrections of continuous many-body systems with open boundary conditions.