Merge pull request brucefan1983#759 from brucefan1983/doc_nep5

doc for NEP5

doc/nep/input_files/nep_in.rst

@@ -7,7 +7,7 @@
 
 This file specifies hyperparameters used for training neuroevolution potential (:term:`NEP`) models, the functional form of which is outline :ref:`here <nep_formalism>`.
 The :term:`NEP` approach was proposed in [Fan2021]_ (NEP1) and later improved in [Fan2022a]_ (NEP2) and [Fan2022b]_ (NEP3).
-Currently, we support NEP3 and NEP4 (to be published), which can be chosen by the :ref:`version keyword <kw_version>`.
+Currently, we support NEP3, NEP4 (to be published), and NEP5 (to be published), which can be chosen by the :ref:`version keyword <kw_version>`.
 
 File format
 -----------
@@ -35,7 +35,7 @@ Keywords
    * - Keyword
      - Brief description
    * - :ref:`version <kw_version>`
-     - select between NEP3 and NEP4
+     - select the NEP version
    * - :ref:`type <kw_type>`
      - number of atom types and list of chemical species
    * - :ref:`type_weight <kw_type_weight>`

doc/nep/input_parameters/version.rst

@@ -10,7 +10,7 @@ The syntax is::
 
   version <version_number>
 
-Here, :attr:`<version_number>` must be an integer, which can be 3 or 4, corresponding to NEP3 and NEP4, respectively.
+Here, :attr:`<version_number>` must be an integer, which can be 3 or 4 or 5, corresponding to NEP3, NEP4, and NEP5, respectively.
 The default is 4.
 
 More information about the :term:`NEP` formalism can be found :ref:`here <nep_formalism>`.

doc/potentials/nep.rst

@@ -6,9 +6,9 @@ Neuroevolution potential
 ************************
 
 The neuroevolution potential (:term:`NEP`) approach was proposed in [Fan2021]_ (NEP1) and later improved in [Fan2022a]_ (NEP2) and [Fan2022b]_ (NEP3).
-Currently, :program:`GPUMD` supports NEP3 and NEP4 (to be published).
-Both versions have comparable accuracy for single-component systems.
-For multi-component systems, NEP4 usually has higher accuracy, if all the other hyperparameters are the same.
+Currently, :program:`GPUMD` supports NEP3, NEP4 (to be published), and NEP5 (to be published).
+All versions have comparable accuracy for single-component systems.
+For multi-component systems, NEP4 and NEP5 usually have higher accuracy, if all the other hyperparameters are the same.
 
 :program:`GPUMD` not only allows one to carry out simulations using :term:`NEP` models via the :ref:`gpumd executable <gpumd_executable>` but even the construction of such models via the :ref:`nep executable <nep_executable>`.
 
@@ -123,6 +123,8 @@ Model dimensions
      - :math:`N_\mathrm{nn} = (N_\mathrm{des} +2) N_\mathrm{neu}+1` (NEP3)
    * -
      - :math:`N_\mathrm{nn} = (N_\mathrm{des} +2) N_\mathrm{neu} N_\mathrm{typ}+1` (NEP4)
+   * -
+     - :math:`N_\mathrm{nn} = ((N_\mathrm{des} +2) N_\mathrm{neu} + 1) N_\mathrm{typ}+1` (NEP5)
 
 The total number of trainable parameters is the sum of the number of trainable descriptor parameters and the number of :term:`NN` parameters :math:`N_\mathrm{nn}`.