Alibaba Group Holding Limited

Jiachen Huang

Jianxin Chen

Michael J Newman

Fang Zhang

Yaoyun Shi

Methods and systems for tensor network contraction are provided. A method implemented by a computing host includes obtaining a plurality of tensor nodes associated with a tensor network and a plurality of indices respectively associated with the plurality of tensor nodes; generating a graph associated with the tensor network, wherein the plurality of tensor nodes correspond to a plurality of vertices of the graph and the plurality of indices correspond to a plurality of edges of the graph, respectively; decomposing the graph into a plurality of sub-graphs; and for each sub-graph of the plurality of sub-graphs, iteratively decomposing a current sub-graph into a plurality of next-tier sub-graphs until a size of each of the plurality of next-tier sub-graphs is less than a pre-set threshold.

Methods and systems for tensor network contraction based on hypergraph decomposition and parameter optimization

One embodiment described herein provides a system and method for simulating behavior of a quantum circuit that includes a plurality of quantum gates. During operation, the system receives information that represents the quantum circuit and constructs an undirected graph corresponding to the quantum circuit. A respective vertex within the undirected graph corresponds to a distinct variable in a Feynman path integral used for computing amplitude of the quantum circuit, and a respective edge corresponds to one or more quantum gates. The system identifies a vertex within the undirected graph that is coupled to at least two two-qubit quantum gates; simplifies the undirected graph by removing the identified vertex, thereby effectively removing the two-qubit quantum gates coupled to the identified vertex; and evaluates the simplified undirected graph, thereby facilitating simulation of the behavior of the quantum circuit.

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Hangzhou, China

Jiachen Huang