In Jones et al, I looked at LSST + existing surveys, including some bumps up in the future for “future improvements”. We didn’t really add NEOCam specific discoveries although the definition of “discovered by another survey” was fairly loose … adding something more NEOCam specific should probably increase the overall completeness somewhat, as one of the cuts for “discovered by another survey” was a solar elongation constraint that would (I think) not be appropriate for NEOCam.
However, you should also look at Grav et al, 2016 - https://arxiv.org/abs/1604.03444 - this is an analysis of LSST completeness, but towards the end it looks at the effect of combining NEOCam and LSST, as well as existing surveys (although it doesn’t go into the details).
I have not updated the current estimate of NEOs of all sizes. The previous estimate is written up in the LSST Science Book (this is citable!), and is based on similar estimates of overall completeness as the newer simulations and an absolute magnitude distribution based on Bottke et al 2002. An update based on orbital and size distributions from something like Granvik et al 2018 (https://www.sciencedirect.com/science/article/pii/S0019103517307017) would probably be appropriate.
One problem with attempting to estimate the total number of objects is that LSST is still about 10% efficient at detecting NEOs with H>25, which is fainter than most reliable estimates of the size distribution go. The same goes with estimates of the MBA population … I suspect that we could be off by as much as a factor of two there (i.e. we could find more than 12M MBAs) if the size distribution is more like that found by SKADS than by SDSS. I haven’t poked at the different NEO size distributions to see what effect that has, but there is at least a 6% uncertainty in the number of NEOs with H<25 (based on Granvik et al 2018).
But yes – this is something I’ve been thinking about updating and making a better estimate of the total number of NEOs (and other types of Solar System objects) detected by LSST, as well the rate of the detections (how many are new detections on an average night, which will change over the lifetime of the survey). I’ll find some time for it at some point!
The LSST survey strategy that produced the (rough) estimate of 100,000 NEOs was not especially NEO-optimized. The only ‘optimization’ that has been somewhat baked into all of the survey strategies explored so far is the time between visits within a night – this interval has been kept relatively short, in order to not let NEOs wander out of the field (obviously… on average). This doesn’t not affect MBAs, but may affect how we link distant objects (even TNOs, to some extent). The advantage is that linking TNOs is relatively easy, with enough observations of the sky, so while I think it’s something we should think about, I’m not overly worried. The survey strategy itself is still evolving and things like block scheduling (which may increase our coverage of contiguous pieces of sky, which was not very good in the simulations used for the NEO completeness estimates) and/or rolling cadence variations may more significantly impact overall discovery rates, particularly for very small + close + fast moving objects. I encourage you to explore this further in a white paper!