form of $$P(f) = P_{\rm aperiodic}(f) + \frac{A_{\rm p}}{\sqrt{2\pi} \omega_{\rm p}} \exp\left[-\frac{(f-f_{\rm p})^2}{2\omega_{\rm p}^2} \right],$$ where $P_{\rm aperiodic}(f)$ is the aperiodic component that can be $P_{\rm SPL}(f)$, $P_{\rm DRW}(f)$, or $P_{\rm BPL}$ in Equations (\[equ\_spl\])-(\[equ\_bpl\]), and the second term [on]{} the right-hand side is the periodic component, which is parameterized to be a Gaussian with free parameters $A_{\rm p}$, $f_{\rm p}$, and $\omega_{\rm p}$. The corresponding period of the light curve is $1/f_{\rm b}$. Since the values of all these three parameters can span a wide range of magnitudes, their prior probabilities are set to be logarithmic. The values of $f_{\rm p}$ are additionally limited by the frequency range of the data.

We tabulate the inferred parameter values for the above periodic PSD models in Table \[tab\_par\]. Remarkably, the center of the Gaussian for the three models corresponds to a period of $\log(P/{\rm years})=1.31, 1.32, 1.25$ respectively, with a typical uncertainty of 0.30 dex. This is in agreement with the period $\log (P/{\rm year}) = 1.3$ from the LS periodogram. In Figure \[fig\_psd\_model\], we show the best recovered PSDs for both aperiodic and periodic models. The Bayes factors for the three periodic models with respect to the (aperiodic) SPL model 