This approach demonstrates effective basis truncation in quantum many-body systems, suggesting improved resource efficiency.
We show how to optimally reduce the local Hilbert basis of lattice quantum many-body (QMB) Hamiltonians. The basis truncation exploits the most relevant eigenvalues of the estimated single-site reduced density matrix (RDM). It is accurate and numerically stable across different model phases, even close to quantum phase transitions. We apply this procedure to different models, such as the Sine-Gordon model, the φ⁴ theory, and lattice gauge theories, namely Abelian U(1) and non-Abelian SU(2), in one and two spatial dimensions. Our results reduce state-of-the-art estimates of computational resources for classical and quantum simulations.
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Majcen et al. (2025) studied this question.
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