Identification and Removal of Noise Modes in Kepler Photometry

TL;DR

The paper introduces TERRA, a new algorithm that identifies and removes instrumental noise from Kepler photometry, significantly improving the detection of Earth-sized exoplanets.

Contribution

TERRA is a novel framework that detects common instrumental noise modes in Kepler data, enhancing the quality of light curves for exoplanet detection.

Findings

Achieves 33 ppm RMS scatter in 12-hour bins for low-noise stars

Enables detection of Earth-sized planet transits as ~3 sigma signals

Improves the sensitivity of Kepler photometry for small exoplanets

Abstract

We present the Transiting Exoearth Robust Reduction Algorithm (TERRA) --- a novel framework for identifying and removing instrumental noise in Kepler photometry. We identify instrumental noise modes by finding common trends in a large ensemble of light curves drawn from the entire Kepler field of view. Strategically, these noise modes can be optimized to reveal transits having a specified range of timescales. For Kepler target stars of low photometric noise, TERRA produces ensemble-calibrated photometry having 33 ppm RMS scatter in 12-hour bins, rendering individual transits of earth-size planets around sun-like stars detectable as ~3 sigma signals.