add microturbulence to simulation

stardis/config_schema.yml

@@ -109,7 +109,11 @@ properties:
                             - van_der_waals
                             - radiation
                         default: []
-                        description: Types of broadening to include.
+                        description: Types of broadening to include.                                              
+                    disable_microturbulence:
+                        type: boolean
+                        default: false
+                        description: Whether to disable microturbulence.
                     broadening_range:
                         type: [quantity, "null"]
                         default: null

stardis/io/base.py

@@ -75,6 +75,8 @@ def parse_config_to_model(config_fname, add_config_dict):
         stellar_model = raw_marcs_model.to_stellar_model(
             adata, final_atomic_number=config.model.final_atomic_number
         )
+        if config.opacity.line.disable_microturbulence:
+            stellar_model.microturbulence = stellar_model.microturbulence * 0.0
 
     elif config.model.type == "mesa":
         raw_mesa_model = read_mesa_model(Path(config.model.fname))

stardis/io/model/marcs.py

@@ -143,8 +143,12 @@ def to_stellar_model(self, atom_data, final_atomic_number=118):
         temperatures = (
             self.data.t.values[::-1] * u.K
         )  # Flip data to move from innermost stellar point to surface
-        # First two none values are old fv_geometry and abundances which are replaced by the new structures.
-        return StellarModel(temperatures, marcs_geometry, marcs_composition)
+        return StellarModel(
+            temperatures,
+            marcs_geometry,
+            marcs_composition,
+            microturbulence=self.metadata["microturbulence"],
+        )
 
 
 def read_marcs_metadata(fpath, gzipped=True):

stardis/model/base.py

@@ -21,14 +21,17 @@ class StellarModel(HDFWriterMixin):
         Composition of the model. Includes density and atomic mass fractions.
     no_of_depth_points : int
         Class attribute to be easily accessible for initializing arrays that need to match the shape of the model.
+    microturbulence : float
+        Microturbulence in km/s.
     """
 
     hdf_properties = ["temperatures", "geometry", "composition"]
 
-    def __init__(self, temperatures, geometry, composition):
+    def __init__(self, temperatures, geometry, composition, microturbulence=0.0):
         self.temperatures = temperatures
         self.geometry = geometry
         self.composition = composition
+        self.microturbulence = microturbulence
 
     @property
     def no_of_depth_points(self):

stardis/radiation_field/opacities/opacities_solvers/broadening.py

@@ -24,7 +24,7 @@
 
 
 @numba.njit
-def _calc_doppler_width(nu_line, temperature, atomic_mass):
+def _calc_doppler_width(nu_line, temperature, atomic_mass, microturbulence):
     """
     Calculates doppler width.
     https://ui.adsabs.harvard.edu/abs/2003rtsa.book.....R/
@@ -51,13 +51,18 @@ def _calc_doppler_width(nu_line, temperature, atomic_mass):
     return (
         nu_line
         / SPEED_OF_LIGHT
-        * math.sqrt(2.0 * BOLTZMANN_CONSTANT * temperature / atomic_mass)
+        * (
+            math.sqrt(
+                2.0 * BOLTZMANN_CONSTANT * temperature / atomic_mass
+                + microturbulence**2
+            )
+        )
     )
 
 
 @numba.vectorize(nopython=True)
-def calc_doppler_width(nu_line, temperature, atomic_mass):
-    return _calc_doppler_width(nu_line, temperature, atomic_mass)
+def calc_doppler_width(nu_line, temperature, atomic_mass, microturbulence=0.0):
+    return _calc_doppler_width(nu_line, temperature, atomic_mass, microturbulence)
 
 
 @cuda.jit
@@ -699,6 +704,7 @@ def calculate_broadening(
         stellar_model.composition.nuclide_masses.loc[lines.atomic_number].values[
             :, np.newaxis
         ],
+        stellar_model.microturbulence.cgs.value,
     )
 
     return gammas, doppler_widths
@@ -727,6 +733,7 @@ def calculate_molecule_broadening(
         lines.nu.values[:, np.newaxis],
         stellar_model.temperatures.value,
         molecule_masses,
+        stellar_model.microturbulence.cgs.value,
     )
 
     return gammas, doppler_widths