An optimized determinant algorithm with randomized redundancy elimination and a TensorFlow implementation compute nuclear correlation functions up to A=7 with large speedups, and a few dominant spin-color terms are shown empirically to reproduce the full correlators.
Fast Evaluation of Multi-Hadron Correlation Functions
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abstract
Calculating the values of nuclear correlation functions is computationally intensive due to the fact that the number of terms in a nuclear wave function scales exponentially with atomic number. To speed up this computation, we represent a correlation function as a sum of the determinants of many small matrices, and exploit similarities between the matrices to speed up the calculations of those determinants.
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2024 1verdicts
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Nuclear correlation functions using first-principle calculations of lattice quantum chromodynamics
An optimized determinant algorithm with randomized redundancy elimination and a TensorFlow implementation compute nuclear correlation functions up to A=7 with large speedups, and a few dominant spin-color terms are shown empirically to reproduce the full correlators.