Periodic stellar variability from almost a million NGTS light curves

We analyse 829 481 stars from the Next Generation Transit Survey (NGTS) to extract variability periods. We utilize a generalization of the autocorrelation function (the G-ACF), which applies to irregularly sampled time series data. We extract variability periods for 16 880 stars from late-A through to mid-M spectral types and periods between similar to 0.1 and 130 d with no assumed variability model. We find variable signals associated with a number of astrophysical phenomena, including stellar rotation, pulsations, and multiple-star systems. The extracted variability periods are compared with stellar parameters taken from Gaia DR2, which allows us to identify distinct regions of variability in the Hertzsprung-Russell Diagram. We explore a sample of rotational main-sequence objects in period-colour space, in which we observe a dearth of rotation periods between 15 and 25 d. This 'bi-modality' was previously only seen in space-based data. We demonstrate that stars in sub-samples above and below the period gap appear to arise from a stellar population not significantly contaminated by excess multiple systems. We also observe a small population of long-period variable M-dwarfs, which highlight a departure from the predictions made by rotational evolution models fitted to solar-type main-sequence objects. The NGTS data spans a period and spectral type range that links previous rotation studies such as those using data from Kepler, K2, and MEarth.

Automated summary

In this study, we analysed over 829,481 stars using data from the Next Generation Transit Survey (NGTS) to extract their variability periods. By comparing the extracted periods with stellar parameters from Gaia DR2, we were able to identify distinct regions of variability in the Hertzsprung-Russell Diagram. We also observed variable signals associated with various astrophysical phenomena and discovered a dearth of rotation periods in a specific range, which had previously only been seen in space-based observations.