论文标题
用于因果环的变异量子本图和定向的无环图
Variational quantum eigensolver for causal loop Feynman diagrams and directed acyclic graphs
论文作者
论文摘要
我们提出了一种用于有效的loop-tree二元性（LTD）中多型feynman图因果关系有效的量子量子算法（VQE）算法，或等效地，在有线图中选择了acyclic构型的选择。 VQE最小化了基于描述多核拓扑的邻接矩阵，其不同的能级对应于循环的数量，以识别一个因果或无环形配置，其不同的能级对应于周期的循环。该算法已被调整为选择多个退化的最小值，从而达到更高的检测率。详细讨论了与基于Grover的算法的性能比较。一般而言，VQE方法要求其实施量较少，而较短的电路则较少，尽管成功率较小。
We present a variational quantum eigensolver (VQE) algorithm for the efficient bootstrapping of the causal representation of multiloop Feynman diagrams in the Loop-Tree Duality (LTD) or, equivalently, the selection of acyclic configurations in directed graphs. A loop Hamiltonian based on the adjacency matrix describing a multiloop topology, and whose different energy levels correspond to the number of cycles, is minimized by VQE to identify the causal or acyclic configurations. The algorithm has been adapted to select multiple degenerated minima and thus achieves higher detection rates. A performance comparison with a Grover's based algorithm is discussed in detail. The VQE approach requires, in general, fewer qubits and shorter circuits for its implementation, albeit with lesser success rates.
