Upper Limits to Long-Term Variability of Solar-Type Stars from Observations of the Open Cluster M67

TL;DR

This study uses observations of the open cluster M67 to estimate the long-term luminosity variability of solar-type stars, providing constraints relevant to Earth's paleoclimate changes over millions of years.

Contribution

It introduces a method to estimate solar-type stars' long-term variability using main sequence width measurements from cluster data, improving understanding of stellar influence on climate.

Findings

Measured main sequence width consistent with a variability sigma of 0.100-0.135.

Estimated photometric noise contribution sigma of about 0.101.

Set upper limits on intrinsic stellar variability between 0.058 and 0.089.

Abstract

Variations in the luminosity of the Sun on timescales of thousands to millions of years could potentially be responsible for terrestrial climate variations in the Phanerozooic geological period (last 540 million years). In this paper, I consider a method that utilizes observations of an open star cluster with approximately the age of the Sun, specifically M67, with data taken from Geller (2015). The idea is to measure the width of the main sequence in the region of solar-type stars, here generously defined to be about spectral class G0 - K1. This width gives an estimate of the dispersion in absolute magnitude of nominally solar-type stars. The sample used consists of 170 solar-type main sequence stars which are not known to be binaries. With this sample, I form an empirical measurement of the width of the main sequence, which is compared with a theoretical expression from Spangler (2025). The measured spread is consistent with a value of sigma, the normalized Gaussian variability of the primary and (if present) secondary star, in the range of 0.100 - 0.135. However, the expected value of sigma from purely photometric noise is estimated as 0.101. Generous upper limits to the intrinsic variability contribution to the inferred width are sigma in the range 0.058-0.089. These limits are not totally devoid of interest in a paleoclimatic context. However, major improvements in the technique are possible with the use of existing data sets from space astronomy missions such as Gaia and Kepler.