Tensor networks for quantum computing

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.

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Cited by in corpus (5)

• Quantum generative modeling for financial time series with temporal correlations
• Simulating Quantum Circuits with Tree Tensor Networks using Density-Matrix Renormalization Group Algorithm
• Harnessing Quantum Dynamics for Robust and Scalable Quantum Extreme Learning Machines
• Distributing Quantum Computations, Shot-wise
• Quantum annealing and condensed matter physics