mindspore.ops.Dihedral14LJAtomEnergy

class mindspore.ops.Dihedral14LJAtomEnergy(nb14_numbers, atom_numbers)[source]

Add the potential energy caused by Lennard-Jones energy correction for each necessary dihedral 1,4 terms to the total potential energy of each atom.

The calculation formula is the same as operator Dihedral14LJEnergy().

Because there is a large amount of inputs and each of them are related, there is no way to construct Examples using random methods. For details, refer the webpage SPONGE in MindSpore.

Parameters

  • nb14_numbers (int32) – the number of necessary dihedral 1,4 terms m.

  • atom_numbers (int32) – the number of atoms n.

Inputs:

  • uint_crd_f (Tensor) - The unsigned int coordinate value of each atom. The data type is uint32 and the shape is \((n, 3)\).

  • LJ_type (Tensor) - The Lennard-Jones type of each atom. The data type is int32 and the shape is \((n,)\).

  • charge (Tensor) - The charge of each atom. The data type is float32 and the shape is \((n,)\).

  • boxlength_f (Tensor) - The length of molecular simulation box in 3 dimensions. The data type is float32 and the shape is \((3,)\).

  • a_14 (Tensor) - The first atom index of each dihedral 1,4 term. The data type is int32 and the shape is \((m,)\).

  • b_14 (Tensor) - The second atom index of each dihedral 1,4 term. The data type is int32 and the shape is \((m,)\).

  • lj_scale_factor (Tensor) - The scale factor for the Lennard-Jones part of force correction of each dihedral 1,4 term. The data type is float32 and the shape is \((m,)\).

  • cf_scale_factor (Tensor) - The scale factor for the Coulomb part of force correction for each dihedral 1,4 terms. The data type is float32 and the shape is \((m,)\).

  • LJ_type_A (Tensor) - The A parameter in Lennard-Jones scheme of each atom pair type. q is the number of atom pair. The data type is float32 and the shape is \((q,)\).

  • LJ_type_B (Tensor) - The B parameter in Lennard-Jones shceme of each atom pair type. q is the number of atom pair. The data type is float32 and the shape is \((q,)\).

Outputs:

  • ene (Tensor) - The accumulated potential energy of each atom. The data type is float32 and the shape is \((n,)\).

Supported Platforms:

GPU