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We introduce a novel extrapolation algorithm inspired by quantum mechanicsand evaluate its performance against linear prediction. Our method involvesmapping function values onto a quantum state and estimating future functionvalues by minimizing entanglement entropy. We demonstrate the effectiveness ofour approach on various simple functions, both with and without noise,comparing it to linear prediction. Our results show that the proposed algorithmproduces extrapolations comparable to linear prediction, while exhibitingimproved performance for functions with sharp features.

A Novel Method of Function Extrapolation Inspired by Techniques in Low-entangled Many-body Physics