Tensor-networks for High-order Polynomial Approximation: A Many-body Physics Perspective

Tong Yang

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arXiv · 2204.07743

Tensor-networks for High-order Polynomial Approximation: A Many-body Physics Perspective

Tong Yang

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Abstract

We analyze the problem of high-order polynomial approximation from a many-body physics perspective, and demonstrate the descriptive power of entanglement entropy in capturing model capacity and task complexity. Instantiated with a high-order nonlinear dynamics modeling problem, tensor-network models are investigated and exhibit promising modeling advantages. This novel perspective establish a connection between quantum information and functional approximation, which worth further exploration in future research.

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quant-ph cond-mat.dis-nn cs.LG cs.NA math.NA

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Tong Yang. 2022-04-16. Tensor-networks for High-order Polynomial Approximation: A Many-body Physics Perspective. https://arxiv.org/abs/2204.07743

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