Earth-like planet searches are underway which can measure the motion of small planets around distant stars. However, investments in these instruments will not meet their full potential without advances in computer software. Through a three year award, a team led by the Universities of Delaware and Chicago will adapt a time domain data analysis tool previously used for health science and solar science for astronomy. Developing new analysis methods will save telescope time that costs tens of thousands of dollars per night by reducing the number of observations needed and increasing telescope efficiency. Students will be involved in the planet searches. The Team's goals are to involve physics and astronomy majors with all levels of academic preparation in planet searches and to create a supportive environment in which students can seek help from a faculty, scholars, and each other. <br/><br/>While the Lomb-Scargle periodogram is foundational to astronomy, it has a significant short-coming: its variance does not decrease as more data are acquired. Statisticians have a 60-year history of developing variance-suppressing power spectrum estimators, but most are not used in astronomy because they are formulated for time series with uniform observing cadence and without seasonal or daily gaps. The team will mitigate the false-positive and bias problems of the Lomb-Scargle periodogram by adapting the multitaper power spectrum estimator for ground-based astronomical time series. They will present multitaper Magnitude-Squared Coherence (MSC) as a diagnostic of oscillations that manifest jointly in two or more observables. MSC between activity indicators and radial velocity is a powerful tool for identifying stellar rotation and harmonics, which have been responsible for many false positive planet detections. They will introduce a non-multitaper version of complex demodulation for ground-based time series. Complex demodulation, a local Fourier decomposition that reconstructs the long-period component of two coupled oscillations, can distinguish activity-modulated stellar signals from non-modulated planetary signals and recover full-phase rotation signals from observations of pulsating stars. This award funds development of the Oscillation Recognition and CAtegorization Software (ORCAS) package, which will contain python and Julia implementations of our frequency-domain methods. ORCAS will be sustainably hosted on bitbucket and registered with the Astrophysical Source Code Library. The methods developed can be applied to planet hunting, seismology, paleoclimatology, genetics, laser Doppler velocimetry, and the Rubin Observatory Legacy Survey of Space and Time.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.