Machine learning is used to optimize coefficients in finite-temperature Fermi-operator expansions, enabling order-of-magnitude faster density matrix calculations on GPUs via matrix multiplications and affine rescaling.
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Machine-learned, finite temperature Fermi-operator expansions suitable for GPUs and AI-hardware
Machine learning is used to optimize coefficients in finite-temperature Fermi-operator expansions, enabling order-of-magnitude faster density matrix calculations on GPUs via matrix multiplications and affine rescaling.