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Bouland, Adam; Fefferman, Bill; Ghosh, Soumik; Metger, Tony; Vazirani, Umesh; Zhang, Chenyi; Zhou, Zixin (, Schloss Dagstuhl – Leibniz-Zentrum für Informatik)Santhanam, Rahul (Ed.)Given a local Hamiltonian, how difficult is it to determine the entanglement structure of its ground state? We show that this problem is computationally intractable even if one is only trying to decide if the ground state is volume-law vs near area-law entangled. We prove this by constructing strong forms of pseudoentanglement in a public-key setting, where the circuits used to prepare the states are public knowledge. In particular, we construct two families of quantum circuits which produce volume-law vs near area-law entangled states, but nonetheless the classical descriptions of the circuits are indistinguishable under the Learning with Errors (LWE) assumption. Indistinguishability of the circuits then allows us to translate our construction to Hamiltonians. Our work opens new directions in Hamiltonian complexity, for example whether it is difficult to learn certain phases of matter.more » « less
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Bouland, Adam; Getachew, Yosheb M.; Jin, Yujia; Sidford, Aaron; Tian, Kevin (, Proceedings of the 40th International Conference on Machine Learning (ICML 2023))
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Bouland, Adam; Fefferman, Bill; Landau, Zeph; Liu, Yunchao (, 2021 IEEE 62nd Annual Symposium on Foundations of Computer Science (FOCS))
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