Segmented-Polynomial-fitting Least Squares (SPLS): An optimized algorithm to find Earth twins

TL;DR

The paper introduces SPLS, an optimized algorithm for detecting Earth-like exoplanets with long, shallow transits by fitting planetary signals and background noise simultaneously, improving detection rates especially for low-SNR, long-period signals.

Contribution

SPLS is a novel segmented polynomial fitting algorithm that enhances exoplanet detection by optimizing trend removal and signal assessment, outperforming traditional methods in challenging scenarios.

Findings

SPLS achieves at least 22.6% higher true positive rate than traditional methods for long-period, low-SNR signals.

The algorithm recovers 97% of true signals in Kepler single-planet systems.

SPLS improves detection of Earth twins in future space missions.

Abstract

Detecting Earth twins remains challenging because their shallow, long-period transits are difficult to distinguish from background noise. Motivated by the challenge, we developed Segmented-Polynomial-fitting Least Squares (SPLS), a new algorithm that simultaneously fits planetary transits and background trends using a segmented double polynomial model. Prior to signal detection, the optimal polynomial order for the trend component is selected using Bayes factor-based model comparison. During the periodogram search, the Signal Detection Efficiency metric is used to assess signal significance. The algorithm is accelerated by a three-step approximation and nonlinear parameter sampling tailored to SPLS. We compare the performance of SPLS with traditional detrending-detection approaches across different orbital periods, signal-to-noise ratios (SNR), planet radii and stellar noise levels on an injection-recovery test. When detecting signals with periods between 10 and 480 days and SNRs below 9, SPLS achieves at least a 22.6% higher true positive rate than other methods at the same 10% false positive rate. Using the threshold determined from the Receiver Operating Characteristic curve analysis, our method also recovers the most true signals while yielding the fewest false positives among all injected samples, and reaches a 97% recovery fraction in Kepler confirmed single-planet systems. The tests demonstrate that SPLS improves the detection of transiting planets, particularly for low-SNR, long-period signals. It offers the potential for finding Earth twins in future applications to data from Kepler, TESS, and upcoming PLATO and Earth 2.0 missions.