Added support for the ACE backend.

README.md

@@ -94,7 +94,8 @@ support the use of
 [DeePMD-kit](https://docs.deepmodeling.com/projects/deepmd/en/master/index.html),
 [ORCA](https://sites.google.com/site/orcainputlibrary/interfaces-and-qmm),
 [SQM](https://ambermd.org/AmberTools.php),
-[XTB](https://xtb-docs.readthedocs.io/en/latest), or
+[XTB](https://xtb-docs.readthedocs.io/en/latest),
+[ACE]( https://acesuit.github.io/) (implemented using [PyJulip](https://github.com/casv2/pyjulip)), or
 [PySander](https://ambermd.org/AmberTools.php)
  for the backend, providing reference MM or QM with EMLE embedding, and pure EMLE
 implementations. To specify a backend, use the `--backend` argument when launching

bin/emle-server

@@ -76,6 +76,7 @@ save_settings = os.getenv("EMLE_SAVE_SETTINGS")
 orca_template = os.getenv("EMLE_ORCA_TEMPLATE")
 deepmd_model = os.getenv("EMLE_DEEPMD_MODEL")
 rascal_model = os.getenv("EMLE_RASCAL_MODEL")
+ace_model = os.getenv("EMLE_ACE_MODEL")
 parm7 = os.getenv("EMLE_PARM7")
 try:
     lambda_interpolate = [
@@ -122,6 +123,7 @@ env = {
     "device": device,
     "deepmd_model": deepmd_model,
     "rascal_model": rascal_model,
+    "ace_model": ace_model,
     "lambda_interpolate": lambda_interpolate,
     "interpolate_steps": interpolate_steps,
     "parm7": parm7,
@@ -217,6 +219,12 @@ parser.add_argument(
     help="path to Rascal model file",
     required=False,
 )
+parser.add_argument(
+    "--ace-model",
+    type=str,
+    help="path to ACE model file",
+    required=False,
+)
 parser.add_argument(
     "--lambda-interpolate",
     type=float,

emle/emle.py

@@ -344,6 +344,7 @@ class EMLECalculator:
         "sander",
         "sqm",
         "xtb",
+        "ace",
         "external",
     ]
 
@@ -369,6 +370,7 @@ def __init__(
         mm_charges=None,
         deepmd_model=None,
         rascal_model=None,
+        ace_model=None,
         parm7=None,
         qm_indices=None,
         sqm_theory="DFTB3",
@@ -428,6 +430,10 @@ def __init__(
             Path to the Rascal model file used to apply delta-learning corrections
             to the in vacuo energies and gradients computed by the backed.
 
+        ace_model : str
+            Path to the ACE model file to use for in vacuo calculations. This
+            must be specified if "ace" is the selected backend.
+
         lambda_interpolate : float, [float, float]
             The value of lambda to use for end-state correction calculations. This
             must be between 0 and 1, which is used to interpolate between a full MM
@@ -732,6 +738,26 @@ def __init__(
             # Flag that delta-learning corrections will be applied.
             self._is_delta = True
 
+        # Validate and load the ACE model.
+        if ace_model is not None:
+            if not isinstance(ace_model, str):
+                raise TypeError("'ace_model' must be of type 'str'")
+
+            # Convert to an absolute path.
+            abs_ace_model = os.path.abspath(ace_model)
+
+            # Make sure the model file exists.
+            if not os.path.isfile(abs_ace_model):
+                raise IOError(f"Unable to locate ACE model file: '{ace_model}'")
+
+            # Load the model.
+            try:
+                import pyjulip
+
+                self._ace_calc = pyjulip.ACE(abs_ace_model)
+            except:
+                raise RuntimeError("Unable to create ACE calculator!")
+
         if restart is not None:
             if not isinstance(restart, bool):
                 raise TypeError("'restart' must be of type 'bool'")
@@ -974,6 +1000,7 @@ def __init__(
             "mm_charges": None if mm_charges is None else self._mm_charges.tolist(),
             "deepmd_model": deepmd_model,
             "rascal_model": rascal_model,
+            "ace_model": ace_model,
             "parm7": parm7,
             "qm_indices": None if qm_indices is None else self._qm_indices,
             "sqm_theory": sqm_theory,
@@ -1121,6 +1148,15 @@ def run(self, path=None):
                         "Failed to calculate in vacuo energies using XTB backend!"
                     )
 
+            # ACE.
+            elif self._backend == "ace":
+                try:
+                    E_vac, grad_vac = self._run_ace(atoms)
+                except:
+                    raise RuntimeError(
+                        "Failed to calculate in vacuo energies using ACE backend!"
+                    )
+
         # External backend.
         else:
             try:
@@ -2810,6 +2846,50 @@ def _run_xtb(atoms):
 
         return energy, gradient
 
+    @staticmethod
+    def _run_ace(atoms):
+        """
+        Internal function to compute in vacuo energies and gradients using
+        ACE (via PyJulip).
+
+        Parameters
+        ----------
+
+        atoms : ase.atoms.Atoms
+            The atoms in the QM region.
+
+        Returns
+        -------
+
+        energy : float
+            The in vacuo ML energy in Eh.
+
+        gradients : numpy.array
+            The in vacuo gradient in Eh/Bohr.
+        """
+
+        if not isinstance(atoms, ase.Atoms):
+            raise TypeError("'atoms' must be of type 'ase.atoms.Atoms'")
+
+        # ACE requires periodic box information so we translate the atoms so that
+        # the lowest (x, y, z) position is zero, then set the cell to the maximum
+        # position.
+        atoms.positions -= np.min(atoms.positions, axis=0)
+        atoms.cell = np.max(atoms.positions, axis=0)
+
+        # Bind the calculator to the atoms.
+        atoms.calc = self._ace_calc
+
+        # Get the energy and forces in atomic units.
+        energy = atoms.get_potential_energy()
+        forces = atoms.get_forces()
+
+        # Convert to Hartree and Eh/Bohr.
+        energy *= EV_TO_HARTREE
+        gradient = -forces * EV_TO_HARTREE * BOHR_TO_ANGSTROM
+
+        return energy, gradient
+
     def _run_rascal(self, atoms):
         """
         Internal function to compute delta-learning corrections using Rascal.

environment.yaml

@@ -16,4 +16,6 @@ dependencies:
   - torchani
   - xtb-python
   - pip:
+    - julia
     - git+https://github.com/lab-cosmo/librascal.git
+    - git+https://github.com/casv2/pyjulip.git