Assessing Quasi‐Periodicities in Jovian X‐Ray Emissions: Techniques and Heritage Survey. Issue 11 (13th November 2018) - Jackman, C. M.; Knigge, C.; Altamirano, D.; Gladstone, R.; Dunn, W.; Elsner, R.; Kraft, R.; Branduardi‐Raymont, G.; Ford, P.
Abstract: Jupiter's auroral X‐rays are rather mysterious, with an unknown driver, and several previous reports of individual cases of quasi‐periodic emission. In this work we revisit heritage X‐ray data sets from the 1990s to 2015 and apply robust significance testing of emerging quasi‐periodicities, seeking to understand the robustness and regularity of previously reported quasi‐periodic emissions. Our analysis incorporates the use of the Rayleigh test as an alternative to Lomb‐Scargle analysis or Fast Fourier Transforms, where Rayleigh is particularly suited to a time‐tagged data set of sparse counts such as is common for jovian X‐ray data. Furthermore, the analysis techniques that we present (including Rayleigh testing and Monte Carlo simulation) can be applied to any time‐tagged data set. The code to conduct such analysis is released as supplementary information to accompany this paper. The five most significant ( p value <0.01) quasi‐periods from Jupiter's northern auroral region have periods ranging from ~8.0 to 45.96 min, and the two most significant ( p value <0.01) quasi‐periods from the south have periods of ~14.1 and ~34.9 min. The selection of a restrictive hot spot source region seems to be critical for detecting quasi‐periodic emission, suggesting that the site of pulsations may be spatially localized. Periods vary from one Jupiter rotation to the next in one long observation, and the north and south are shown to pulse independently in another conjugate observation. These results have important implications for understanding the driver of jovian X‐ray emission. Key Points: Timing analysis of Chandra observations of Jupiter's X‐ray auroras from 1999 to 2015 Statistically significant quasi‐periodicities in jovian auroral X‐rays are relatively rare and periods variable, even on successive planetary rotations We use Rayleigh testing and Monte Carlo simulation to search for statistically significant quasi‐periods in sparse, time‐tagged data