Adding option for Fermi-Dirac statistics

Author: marc-flex

CHANGELOG.md

@@ -18,6 +18,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - New `LobeMeasurer` tool in the `microwave` plugin that locates lobes in antenna patterns and calculates lobe measures like half-power beamwidth and sidelobe level.
 - Validation step that raises a `ValueError` when no frequency-domain monitors are present, preventing invalid adjoint runs.
 - Metal surface roughness models: modified Hammerstad, Huray Snowball, and Cannonball-Huray.
+- Support for Fermi-Dirac statistics in Charge solver. This option can be activated when defining the analysis type `IsothermalSteadyChargeDCAnalysis` with `fermi_dirac=True`. This option will provide more accurate results in simulations where very high doping may lead the pseudo-Fermi energy levels to approach either the conduction or the valence energy levels.
 
 ### Changed
 

tests/test_components/test_heat_charge.py

@@ -962,6 +962,7 @@ def charge_tolerance(self):
         return td.IsothermalSteadyChargeDCAnalysis(
             temperature=300,
             tolerance_settings=td.ChargeToleranceSpec(rel_tol=1e5, abs_tol=1e3, max_iters=400),
+            fermi_dirac=True,
         )
 
     @pytest.fixture(scope="class")

tidy3d/components/spice/analysis/dc.py

@@ -39,6 +39,14 @@ class ChargeToleranceSpec(Tidy3dBaseModel):
         "or when the tolerance criteria has been met.",
     )
 
+    ramp_up_iters: pd.PositiveInt = pd.Field(
+        default=5,
+        title="Ramp-up iterations.",
+        description="In order to help in start up, quantities such as doping "
+        "are ramped up until they reach their specified value. This parameter "
+        "determines how many of this iterations it takes to reach full values.",
+    )
+
 
 class IsothermalSteadyChargeDCAnalysis(Tidy3dBaseModel):
     """
@@ -65,3 +73,12 @@ class IsothermalSteadyChargeDCAnalysis(Tidy3dBaseModel):
         "at `convergence_dv` intervals until the required bias is reached. This is, therefore, a "
         "convergence parameter in DC computations.",
     )
+
+    fermi_dirac: bool = pd.Field(
+        False,
+        title="Fermi-Dirac statistics",
+        description="Determines whether Fermi-Dirac statistics are used. When False, "
+        "Boltzmann statistics will be used. This can provide more accurate results in situations "
+        "where very high doping may lead the pseudo-Fermi energy level to approach "
+        "either the conduction or valence energy bands.",
+    )