GainMedium

GainMedium combines a MeshTopology with the material and state arrays that the ASE calculation needs.

from HASEonGPU import GainMedium

medium = GainMedium(topology=topology)

Physical Properties

The most important pattern is to ask the property object for its expected shape, then create an array with that shape:

beta_shape = medium.get("betaCells").expectedShape
medium.get("betaCells").value = np.zeros(beta_shape)

You can set several properties at once:

medium.withPhysicalProperties(
    betaCells=np.zeros(medium.get("betaCells").expectedShape),
    betaVolume=np.zeros(medium.get("betaVolume").expectedShape),
    claddingCellTypes=np.zeros(medium.get("claddingCellTypes").expectedShape, dtype=np.uint32),
    refractiveIndices=[2.0, 1.0, 2.0, 1.0],
    reflectivities=np.zeros(medium.get("reflectivities").expectedShape),
    nTot=2.776e20,
    crystalTFluo=9.41e-4,
    claddingNumber=1,
    claddingAbsorption=5.5,
)

withPhysicalProperties returns the same GainMedium instance, so it can be chained.

Property Reference

betaCells: Excited-state fraction \(\beta_i\) at topology points and z-levels. Matrix shape: (numberOfPoints, numberOfLevels).
betaVolume: Prism-centered excited-state fraction \(\beta_j\) used by the ASE ray integration. Matrix shape: (numberOfTriangles, numberOfLevels - 1).
claddingCellTypes: Triangle-wise cladding type index. Shape: (numberOfTriangles,).
refractiveIndices: Four refractive indices: [bottomInside, bottomOutside, topInside, topOutside].
reflectivities: Surface reflectivity per triangle. Matrix shape: (2, numberOfTriangles) where row 0 is bottom and row 1 is top.
nTot: Total active-ion concentration \(N_{\mathrm{tot}}\) in cm^-3.
crystalTFluo: Fluorescence lifetime \(\tau\).
claddingNumber: Cladding type selected for cladding absorption handling.
claddingAbsorption: Absorption coefficient of the selected cladding.

Shape and Metadata Utilities

get(name) returns a property wrapper:

prop = medium.get("betaCells")
prop.name
prop.description
prop.dtype
prop.expectedShape
prop.value
prop.meta()

listProperties() returns metadata for all known physical properties:

for prop in medium.listProperties():
    print(prop["name"], prop["expectedShape"], prop["isSet"])

set(name, value) validates and stores one property:

medium.set("nTot", 2.776e20)
medium.set("betaCells", np.zeros(medium.get("betaCells").expectedShape))

Arrays can be supplied either in matrix shape or flat Fortran order. Stored arrays are flattened internally for the HASEonGPU binding.

Indexing Helpers

GainMedium forwards beta-cell coordinate lookups for \(\beta_i\) to its topology:

i, k = medium.betaCellIndexAt(x=0.0, y=0.0, z=0.0)
beta = medium.get("betaCells").value.reshape(
    medium.get("betaCells").expectedShape,
    order="F",
)
beta[i, k] = 0.5
medium.get("betaCells").value = beta

Convenience Dimensions

medium.numberOfPoints
medium.numberOfTriangles
medium.numberOfPrisms
medium.numberOfLevels

emptyBetaCells(fill=0.0) creates a correctly shaped beta array \(\beta_i\):

medium.get("betaCells").value = medium.emptyBetaCells(fill=0.0)