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ABACUS develop
Atomic-orbital Based Ab-initio Computation at UStc
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Implementation of ESolver_DP class for DeePMD method. More...
#include "esolver_dp.h"#include "source_base/parallel_common.h"#include "source_base/timer.h"#include "source_io/output_log.h"#include "source_io/cif_io.h"#include <iomanip>#include <sstream>#include <unordered_map>Implementation of ESolver_DP class for DeePMD method.
#include "source_io/module_parameter/parameter.h"
This file contains the implementation of the ESolver_DP class, which is used for solving the energy and forces in a Deep Potential Molecular Dynamics (DeePMD) simulation. DeePMD is a method for training deep neural networks to accurately predict the potential energy surface of a molecular system.
For more information about DeePMD, see the following reference:
Han Wang, Linfeng Zhang, Jiequn Han, and Roberto Car. "DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics," Computer Physics Communications 228, 178-184 (2018). https://doi.org/10.1016/j.cpc.2018.03.016