Abstract

Complexity is often invoked alongside size and mass as a characteristic of macroscopic quantum objects. In 2004, Aaronson introduced the \textit{tree size} (TS) as a computable measure of complexity and studied its basic properties. In this paper, we improve and expand on those initial results. In particular, we give explicit characterizations of a family of states with superpolynomial complexity nΩ(log⁡n)=TS=O(n!)n^{Ω(\log n)}= \mathrm{TS} =O(\sqrt{n}!) in the number of qubits nn; and we show that any matrix-product state whose tensors are of dimension D×DD\times D has polynomial complexity TS=O(nlog⁡22D)\mathrm{TS}=O(n^{\log_2 2D}).

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