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An Update on the Effects of Results from Wide-field Surveys on Asteroid Rotation Statistics

Presentation #211.06 in the session “Asteroid Surveys: Sifting through the Data”.

Published onOct 26, 2020
An Update on the Effects of Results from Wide-field Surveys on Asteroid Rotation Statistics

In 2015 we (Warner et al., DPS 2015) examined the effects of including the results from large wide-field surveys on asteroid rotation statistics. At the time, the two main contributors were Waszczak et al. (2015) and Chang et al. (2015, 2016), who used ground-based observations from the Palomar Transient Factory. Five years later, several other surveys have contributed to the pool of rotation periods, e.g., Pal et al. (2019), Erasmus et al. (2018, 2019, 2020). Some of these are space-based observations from Kepler and TESS.

A common trait of the surveys is a low “success rate,” i.e., the number of objects for which a lightcurve was found, even if not a unique solution, versus the number of objects observed. Based on this metric, the surveys usually achieved no better than about a 20% success rate, sometimes as low as 10-12%. This means that no less than 80%, i.e., tens of thousands of objects, failed outright. This did and still introduces significant selection effects (the “easy” targets have a higher success rate) such that the “successful” results likely do not accurately reflect rotation statistics.

We present our analysis of rotation statistics with and without the inclusion of the wide-fields surveys. As before, we found a bias towards larger amplitude lightcurves and a different distribution of rotation frequencies when compared to dense lightcurve results obtained by ground-based programs with “dense” meaning tens of observations each night for as many nights as needed to find a period or determine one cannot be found.

On the plus side, the spaced-based surveys show a significant increase in the number of objects with P > 24 h because they can avoid issues associated with Earth-day commensurate periods and long breaks due to weather or other factors. These results could lead to new understandings about how the YORP effect affects rotation rates.

We urge caution when/if including the results of wide-fields surveys since they cannot be accurately debiased. Instead, the “basic” data set from the asteroid lightcurve database (LCDB; Warner et al., 2009) based on dense photometry should be used initially to check if new results are just “average” or may have a legitimate impact on rotation studies.

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