Simulated annealing for tensor network states
NEW JOURNAL OF PHYSICS(2014)
摘要
Markov chains for probability distributions related to matrix product states and one-dimensional Hamiltonians are introduced. With appropriate 'inverse temperature' schedules, these chains can be combined into a simulated annealing scheme for ground states of such Hamiltonians. Numerical experiments suggest that a linear, i.e., fast, schedule is possible in non-trivial cases. A natural extension of these chains to two-dimensional settings is next presented and tested. The obtained results compare well with Euclidean evolution. The proposed Markov chains are easy to implement and are inherently sign problem free (even for fermionic degrees of freedom).
更多查看译文
关键词
matrix product states,projected entangled pair states,metropolis algorithm,strongly correlated systems
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要