An apodized Kepler periodogram for separating planetary and stellar activity signals.

Area of Science:

• Astronomy and Astrophysics
• Exoplanetary Science
• Data Analysis Techniques

Background:

• Precision radial velocity (RV) measurements are crucial for detecting exoplanets.
• Stellar activity (SA) can mimic or mask planetary signals in RV data, complicating analysis.
• Existing methods struggle to fully disentangle planetary signals from complex stellar noise.

Purpose of the Study:

• To introduce a new apodized Keplerian (AK) model for analyzing RV data.
• To differentiate between planetary signals and stellar activity-induced RV signals.
• To enhance the reliability of exoplanet detection through improved noise modeling.

Main Methods:

• Development of a novel apodized Keplerian (AK) model incorporating a Gaussian apodization function.
• Inclusion of a linear regression term with stellar activity diagnostics (log R'hk).
• Utilization of Bayesian fusion Markov chain Monte Carlo for parameter exploration and a differential generalized Lomb-Scargle periodogram for signal identification.

Main Results:

• The AK model successfully distinguished planetary signals from stellar activity.
• A significant reduction in stellar activity noise by a factor of approximately 6 was achieved.
• Planetary candidate parameters were refined by modeling stellar activity with AK signals.

Conclusions:

• The apodized Keplerian model offers a robust approach to modeling and mitigating stellar activity in RV data.
• This technique improves the precision and reliability of exoplanet detection.
• Further development includes incorporating moving average components for residual correlation analysis.