September 29, 2025Open Access

Tensor networks for quantum computing

Key Points

Tensor networks are pivotal in quantum computing, enhancing simulation and error correction methods.
The application of tensor networks in quantum machine learning showcases their versatility in various domains.
Opportunities in tensor-network techniques point to future advancements in quantum circuit synthesis and optimization.
Challenges in using tensor networks highlight the need for further research and development to fully leverage their potential.

Abstract

In the rapidly evolving field of quantum computing, tensor networks serve as an important tool due to their multifaceted utility. In this paper, we review the diverse applications of tensor networks and show that they are an important instrument for quantum computing. Specifically, we summarize the application of tensor networks in various domains of quantum computing, including simulation of quantum computation, quantum circuit synthesis, quantum error correction and mitigation, and quantum machine learning. Finally, we provide an outlook on the opportunities and the challenges of the tensor-network techniques.

Tensor networks for quantum computing

Key Points

Abstract

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