Response to An empirical examination of WISE/NEOWISE asteroid analysis and results

We show that a number of claims made in Myhrvold (2018) (hereafter M2018b) regarding the WISE data and thermal modeling of asteroids are incorrect. That paper provides thermal fit parameter outputs for only two of the about 150,000 object dataset and does not make a direct comparison to asteroids with diameters measured by other means to assess the quality of that works thermal model. We are unable to reproduce the results for the two objects for which M2018b published its own thermal fit outputs, including diameter, albedo, beaming, and infrared albedo. In particular, the infrared albedos published in M2018b are unphysically low. [...] While there were some minor issues with consistency between tables due to clerical errors in the WISE/NEOWISE teams various papers and data release in the Planetary Data System, and a software issue that slightly increased diameter uncertainties in some cases, these issues do not substantially change the results and conclusions drawn from the data. We have shown in previous work and with updated analyses presented here that the effective spherical diameters for asteroids published to date are accurate to within the previously quoted minimum systematic 1-sigma uncertainty of about 10 percent when data of appropriate quality and quantity are available. Moreover, we show that the method used by M2018b to compare diameters between various asteroid datasets is incorrect and overestimates their differences. In addition, among other misconceptions in M2018b, we show that the WISE photometric measurement uncertainties are appropriately characterized and used by the WISE data processing pipeline and NEOWISE thermal modeling software. We show that the Near-Earth Asteroid Thermal Model (Harris 1998) employed by the NEOWISE team is a very useful model for analyzing infrared data to derive diameters and albedos when used properly.

The Albedo Distribution of Near Earth Asteroids

The cryogenic WISE mission in 2010 was extremely sensitive to asteroids and not biased against detecting dark objects. The albedos of 428 Near Earth Asteroids (NEAs) observed by WISE during its fully cryogenic mission can be fit quite well by a 3 parameter function that is the sum of two Rayleigh distributions. The Rayleigh distribution is zero for negative values, and follows $f(x) = x exp[-x^2/(2sigma^2)]/sigma^2$ for positive x. The peak value is at x=sigma, so the position and width are tied together. The three parameters are the fraction of the objects in the dark population, the position of the dark peak, and the position of the brighter peak. We find that 25.3% of the NEAs observed by WISE are in a very dark population peaking at $p_V = 0.03$, while the other 74.7% of the NEAs seen by WISE are in a moderately dark population peaking at $p_V = 0.168$. A consequence of this bimodal distribution is that the Congressional mandate to find 90% of all NEAs larger than 140 m diameter cannot be satisfied by surveying to H=22 mag, since a 140 m diameter asteroid at the very dark peak has H=23.7 mag, and more than 10% of NEAs are darker than p_V = 0.03.

Modeling the Performance of the LSST in Surveying the Near-Earth Object Population

We have performed a detailed survey simulation of the LSST performance with regards to near-Earth objects (NEOs) using the projects current baseline cadence. The survey shows that if the project is able to reliably generate linked sets of positions and times (a so-called tracklet) using two detections of a given object per night and can link these tracklets into a track with a minimum of 3 tracklets covering more than a ~12 day length-of-arc, they would be able to discover 62% of the potentially hazardous asteroids (PHAs) larger than 140 m in its projected 10 year survey lifetime. This completeness would be reduced to 58% if the project is unable to implement a pipeline using the two detection cadence and has to adopt the four detection cadence more commonly used by existing NEO surveys. When including the estimated performance from the current operating surveys, assuming these would continue running until the start of LSST and perhaps beyond, the completeness fraction for PHAs larger than 140m would be 73% for the baseline cadence and 71% for the four detection cadence. This result is a lower than the estimate of Ivezic et al. (2007,2014); however it is comparable to that of Jones et al. (2016) who show completeness ~70$%. We also show that the traditional method of using absolute magnitude H < 22 mag as a proxy for the population with diameters larger than 140m results in completeness values that are too high by ~5%. Our simulation makes use of the most recent models of the physical and orbital properties of the NEO populations, as well as simulated cadences and telescope performance estimates provided by LSST. We further show that while neither LSST nor a space-based IR platform like NEOCam individually can complete the survey for 140m diameter NEOs, the combination of these systems can achieve that goal after a decade of observation.