Closed SteveOv closed 5 months ago
Currently we use eeps for the stellar models (eeps not in GH, but are picked up from within epob_maven/libs/data/stellar_models/mist/MIST_v1.2_feh_p0.00_afe_p0.0_vvcrit_0.4_EEPS)
Separately we use an ISO file when plotting the H-R diagram for the formal-test-dataset (./config/MIST-v1.2_feh_p0.00_afe_p0.0_vvcrit0.0_basic.iso).
Current thinking is that we should consolidate this functionality, and base it on iso files.
Now we have the potential for post main sequence components it's not always the more massive component which is brighter/gives the primary eclipses. Is there a way of predicting which eclipses will be deeper?
Also need to deprecate the StellarModels class structure.
The synthetic-mist-tess-dataset is derived from synthetic star systems based on MIST 1.2 stellar models. This currently works by random selecting of Z (for which there is one choice) and the initial masses. The system age is selected to be late main-sequence of the more massive star. From this the radii, temps, luminosity and logg are looked up which gives us the info we need for surface brightness calcs and limb darkening lookups. Throw in period, inclination and eccentricity params chosen from random distributions (a la training dataset) and we have everything we need to produce a test light-curve.
The crux of the question being, is this the best way to work with the MIST data?
The models are effectively published in two forms;
The current implementation uses the latter data via a convoluted import process.
Investigate whether it will be simpler to use ISOs. The generator code could select a Z and age value, then two masses from those available in the EEP and then validate that the phases were reasonable (we don't want protostars or remnants, so bias towards M-S) - repeat if there's a problem. With the Z, age and initial masses we're ready to continue with the current generator approach. The benefit; remove the need to pre-process plus the ISO data is more compact.