Lost Sisters Found: TESS and Gaia Reveal a Dissolving Pleiades Complex

Abstract Most star clusters dissolve into the Galaxy over tens to hundreds of millions of years after they form. While recent Gaia studies have honed our view of cluster dispersal, the exact chronology of which star formation events begat which star cluster remnants remains unclear. This problem is acute after 100 Myr, when cluster remnants have spread over hundreds of parsecs and most age estimates for main-sequence stars are too imprecise to link the stars to their birth events. Here we develop a Bayesian framework that combines TESS stellar rotation rates with Gaia kinematics to identify diffuse remnants of open clusters. We apply our method to the Pleiades, which previous studies have noted shows kinematic similarities to other nearby young stellar groups. We find that the Pleiades constitutes the bound core of a much larger, coeval structure that contains multiple known clusters distributed over 600 pc. We refer to this structure as the Greater Pleiades Complex. On the basis of uniform ages, coherent space velocities, detailed elemental abundances, and traceback histories, we conclude that most stars in this complex originated from the same giant molecular cloud. This work establishes a scalable approach for tracing the genealogies of nearby clusters and further cements the Pleiades as a cornerstone of stellar astrophysics. We aim to apply this methodology to other associations as part of the upcoming TESS All-Sky Rotation Survey.

Authors

Publication Details

Journal
The Astrophysical Journal
Published
2025-11-12
DOI
https://doi.org/10.3847/1538-4357/ae0724
Primary Topic
Astrophysics and Star Formation Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Lost Sisters Found: TESS and Gaia Reveal a Dissolving Pleiades Complex

Andrew W. Mann, Andrew W. Boyle, Luke G. Bouma
The Astrophysical Journal
Astrophysics and Star Formation Studies
article

Lost Sisters Found: TESS and Gaia Reveal a Dissolving Pleiades Complex

Andrew W. Mann, Andrew W. Boyle, Luke G. Bouma
article en

Abstract

Abstract Most star clusters dissolve into the Galaxy over tens to hundreds of millions of years after they form. While recent Gaia studies have honed our view of cluster dispersal, the exact chronology of which star formation events begat which star cluster remnants remains unclear. This problem is acute after 100 Myr, when cluster remnants have spread over hundreds of parsecs and most age estimates for main-sequence stars are too imprecise to link the stars to their birth events. Here we develop a Bayesian framework that combines TESS stellar rotation rates with Gaia kinematics to identify diffuse remnants of open clusters. We apply our method to the Pleiades, which previous studies have noted shows kinematic similarities to other nearby young stellar groups. We find that the Pleiades constitutes the bound core of a much larger, coeval structure that contains multiple known clusters distributed over 600 pc. We refer to this structure as the Greater Pleiades Complex. On the basis of uniform ages, coherent space velocities, detailed elemental abundances, and traceback histories, we conclude that most stars in this complex originated from the same giant molecular cloud. This work establishes a scalable approach for tracing the genealogies of nearby clusters and further cements the Pleiades as a cornerstone of stellar astrophysics. We aim to apply this methodology to other associations as part of the upcoming TESS All-Sky Rotation Survey.

The Astrophysical JournalVol. 994(1)
Openalex Percentile: Top 77%
Astrophysics and Star Formation Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.