A structure-preserving low-rank factorization of 2RDMs achieves linear rank scaling with system size and ~99% compression while retaining chemical accuracy for correlated states.
and\ author Barbatti , M
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CUTS-GPR performs numerically exact Gaussian process regression with near-linear scaling in training points N and low-order polynomial scaling in dimensions D by exploiting additive kernels on incomplete grids.
Implements TDDFT-ris with density fitting and approximate Z-vector for fast excited-state gradients and nonadiabatic couplings in FSSH dynamics, claiming negligible errors and high efficiency for medium-sized systems.
citing papers explorer
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Low-rank compression of two-electron reduced density matrices
A structure-preserving low-rank factorization of 2RDMs achieves linear rank scaling with system size and ~99% compression while retaining chemical accuracy for correlated states.
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Don't Get Your Kroneckers in a Twist: Gaussian Processes on High-Dimensional Incomplete Grids
CUTS-GPR performs numerically exact Gaussian process regression with near-linear scaling in training points N and low-order polynomial scaling in dimensions D by exploiting additive kernels on incomplete grids.
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TDDFT Gradients and Nonadiabatic Couplings with Minimal Auxiliary Basis Set Approximation for Fewest-Switches Surface Hopping Dynamics
Implements TDDFT-ris with density fitting and approximate Z-vector for fast excited-state gradients and nonadiabatic couplings in FSSH dynamics, claiming negligible errors and high efficiency for medium-sized systems.