At the stellar noise frontier: A transit survey of 121 TESS M3--M6 dwarfs

TL;DR

This study systematically surveys 121 M3-M6 dwarf stars using recent TESS data, identifying 20 transit-like signals and establishing a framework for reliable detection amid stellar noise.

Contribution

It introduces a comprehensive pipeline combining multiple validation steps, enabling robust detection of transiting planets around newly accessible mid-to-late M-dwarfs.

Findings

Validated pipeline with 100% recovery on known systems

Identified 20 transit-like signals in 16 stars

Classified candidates into tiers based on reliability

Abstract

M-dwarf stars are the most favorable hosts for detecting small transiting planets, yet mid-to-late M-dwarfs that acquired sufficient TESS multi-sector coverage only through recent Cycle 6+ observations represent a newly accessible discovery space. This paper presents a systematic transit survey of 121 M3-M6 dwarfs (Teff = 2700-3400 K) selected as "newly enabled" targets -- stars with <=2 archival TESS sectors that only recently crossed the multi-sector detection threshold, covering P = 0.5-100 d. The sample was selected from 498,312 TIC M-dwarfs via a 9-step funnel. The pipeline combines TLS with a signal validation cascade, TRICERATOPS vetting, Gaia DR3 verification, and three empirical signal reliability tests. Pipeline validation achieved 100% recovery (16/16 planets) on 10 known systems with zero false positives. The survey identifies 20 transit-like signals across 16 systems, none with prior TOI designations. The reliability framework classifies 2 as Tier 1 (High Robustness), 7 as Tier 2 (Moderate), and 10 as Tier 3 (Noise-Susceptible); one monotransit is excluded. No candidate SDE significantly exceeds its host star's noise floor. The global false alarm rate is 17.4% (21/121; Wilson 95% CI: [11.6%, 25.1%]).The 2 Tier 1 candidates are priorities for RV confirmation. The 10 Tier 3 candidates require additional TESS sectors to establish signal persistence; 9 systems need high-resolution imaging.