NEMESIS: Exoplanet Transit Survey of Nearby M-Dwarfs in TESS FFIs I

TL;DR

This study introduces NEMESIS, a new pipeline for analyzing TESS FFI data of nearby M-dwarfs, leading to the discovery of new exoplanet candidates and an improved understanding of planet occurrence rates.

Contribution

The paper presents a novel pipeline, NEMESIS, for extracting photometry and detecting transits in TESS FFI data, resulting in new exoplanet candidates around M-dwarfs.

Findings

Detected 29 planet candidates, 24 of which are new.

Calculated an occurrence rate of 2.49 planets per star for certain period and radius ranges.

Projected 122 transit detections of nearby M-dwarfs.

Abstract

In this work, we present the analysis of 33,054 M-dwarf stars located within 100 parsecs in the Transiting Exoplanet Survey Satellite (TESS) Full Frame Images (FFIs) of the observed sectors 1 to 5. We present a new pipeline called NEMESIS which was developed to extract detrended photometry and perform transit searches of single sector data in TESS FFIs. As many M-dwarfs are faint and are not observed with a 2 minute cadence by TESS, FFI transit surveys can give an empirical validation of how many planets are missed by using the 30 minute cadence data. In this work, we detected 183 threshold crossing events and present 29 planet candidates for sectors 1 to 5, 24 of which are new detections. Our sample contains orbital periods ranging from 1.25 to 6.84 days and planetary radii from 1.26 to 5.31 Earth radii. With the addition of our new planet candidate detections along with previous detections observed in sectors 1 to 5, we calculate an integrated occurrence rate of 2.49 +/- 1.58 planets per star for the period range between [1,9] days and planet radius range between [0.5,11] Earth radii. We project an estimated yield of 122 +/- 11 transit detections of nearby M-dwarfs. 23 of our new candidates have Signal to Noise ratios > 7, Transmission Spectroscopy Metrics > 38 and Emission Spectroscopy Metrics > 10. We provide all of our data products for our planet candidates through the Filtergraph data visualization service located at https://filtergraph.com/NEMESIS.