Rank-adaptive tensor decompositions enable memory-efficient dynamical simulations of Schrödinger's equation by compressing partially entangled quantum states while controlling truncation error via SVD thresholds.
Fast and converged classical simulations of evidence for the utility of quantum computing before fault tolerance.Science Advances, 10(3):eadk4321
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Dynamical Simulations of Schr\"odinger's Equation via Rank-Adaptive Tensor Decompositions
Rank-adaptive tensor decompositions enable memory-efficient dynamical simulations of Schrödinger's equation by compressing partially entangled quantum states while controlling truncation error via SVD thresholds.