Hi all,
The most basic metric for most solar system populations is the fraction that is “Discovered” by LSST, I believe. To that end: having input populations for metrics related to discovery is important!
Okay, so some background information first:
- because of speed limitations for generating observations, I am usually setting the number of orbit in the input population to about 5k
- in general, I am assuming that the orbital elements and the H distribution can be roughly separated (this doesn’t have to be perfect, for most comparison purposes) – so these 5k orbits are cloned over a range of H values when evaluating the MAF discovery metrics. I have found pretty good results when evaluating the MAF metrics with a stepsize of between 0.1 and 0.5 magnitudes, so usually use 0.2, and try use a maximum/minimum H value to capture the place where the discovery flattens out at both max/min values. The exact values and range depend on the population.
- you can choose colors for your objects, via their SEDs [due to how we started and how the machinery works, SEDs are preferred rather than broad-band colors, but we can make fake SEDs from broad-band colors, no problem]
– These new SEDs have to be referenced in the input orbits, and the data file put in the right place, but then that’s it. - I’m not including light curves at the moment. You may find that including a lightcurve is important for a particular metric, but that’s not currently implemented in general.
– HOWEVER, the apparent magnitude for any object at any observation is calculated via a “Stacker” – such as the ones at https://github.com/lsst/sims_maf/blob/feature/updateMoPlots/python/lsst/sims/maf/stackers/moStackers.py
so you can implement different Stackers to calculate apparent magnitudes in different ways (such as for comets or active asteroids) and then use these new calculated magnitudes. You could add a lightcurve Stacker if needed, then you just use that alternative stacker instead of the standard stacker.
So specific populations: (these are what I would like to use going forward, but if you have other suggestions or better suggestions, let’s have that discussion here)
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NEOs : Granvik model ref downloaded from http://www.helsinki.fi/~mgranvik/data/Granvik+_2018_Icarus/ … then subsampled and assigned SEDs from C and S types.
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TNOs: CFEPS L7 model (see http://www.cfeps.net/?page_id=105 and references therein) … subsampled and assigned SEDs (but yes, these SEDs should be updated to be redder)
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Scattered Disk Objects: ref Shankman scattered disk model … subsampled and added SEDs
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MBAs: Grav S3M model ref … based on a version from PanSTARRS, but pretty close to the version available from https://drtgrav.com/research/76-2/ … then subsampled and assigned C and S type SEDs.
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Jovian Trojans: Grav S3M model ref – same reference as above, but this is no longer available on the same webpage. We have a version based on the PanSTARRS model.
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Added soon: Minimoons: Granvik & Fedorets (I will have to find the appropriate reference)
These subsampled & SED-assigned population models can be downloaded at https://epyc.astro.washington.edu/~lynnej/orbits/
Still looking for:
- resonant TNO specific model (if there is a science case highlighted from this)
- active asteroid population model
- comet model
- updated MBA model
- updated Trojan model
- Interstellar Object model
minimoon model - impactor model
- ?
For comets and active asteroids, additional methods for calculating apparent magnitude are also needed.