Poisson level was subtracted from the resulting power spectra. Following @kle04 we first estimated the Poisson noise using the @zha95 formula and then (after inspecting the high frequency range and finding no unexpected features) shifted it to match the level between $\sim3000$–$4000$ Hz, where no intrinsic power should be present, but only counting statistics noise. Then we normalized the power spectra using the rms normalization [@van95]. In this normalization, the integral over the power spectrum is equal to the fractional rms amplitude squared. The power density units are $\rm\,(rms/mean)^{2}Hz^{-1}$ and the fractional rms amplitude in one specific band is: $$\rm\,rms=\it\left[\int_{\nu_{1}}^{\nu_{2}} P(\nu)\, d\nu\right]^{1/2}$$

The errors on the fractional rms are calculated by using the dispersion of points in the data. We consider a measurement as a non-detection in a specific band, when the ratio between the fractional rms and its standard deviation is smaller than 3. In this case we quote upper limits at the 98% confidence level.

The periodic 401 Hz pulsations were analyzed by constructing pulse profiles folding chunks of lightcurve in profiles of $N=32$ bins, with the ephemeris of J1808 provided by @har09. In this folding process we used the TEMPO pulsar timing program (v 11.005) to generate 