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Lookup NU author(s): Keegan Thomson-ParessantORCiD, Dr Dominic BowmanORCiD, Federica Nardini, Dr Laura Scott, Pieterjan Van Daele, Ankur Kalita, Logan Dennis, Jan HennecoORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
A wide range of variability mechanisms exist among intermediate mass and massive stars, which are not yet fully understood. Using complementary data sources for a large population of B- and O-type stars, we aim to study the prevalence and interplay of different types of variability, including binarity, pulsation, and rotation, to prepare for future modelling. To this end, we analyse high-resolution HERMES spectra and 2-min cadence TESS photometry and characterise the diverse variability observed within a population of 873 O- and B-type stars. The spectroscopic data were normalised using machine-learning techniques, compared to a grid of synthetic TLUSTY spectra to determine stellar parameters, and used to identify radial velocity variability. Photometric time series were analysed using standard frequency analysis methods to detect pulsations and rotational modulation signatures. We find that more than 93 per cent of the sample exhibits photometric variability. Photometric variability caused by pulsations is identified in 82 per cent of the sample, with dominant contributions from β Cep and slowly pulsating B-type stars, as well as stochastic low-frequency variability. Based on a limited number of spectroscopic epochs, at least 14 per cent of the stars show evidence of binarity, including both eclipsing and spectroscopic systems. This work represents one of the largest homogeneous surveys of variability for intermediate-mass and massive stars in the Northern hemisphere, and complementing similar efforts in the Southern hemisphere. It provides a statistical framework for future studies of stellar structure and evolution, particularly in the context of asteroseismology.
Author(s): Thomson-Paressant K, Bowman DM, Nardini F, Scott LJA, Bodensteiner J, Shenar T, Mahy L, Handler G, Shitrit N, Arcavi I, Abdul-Masih M, Simon-Diaz S, Van Daele P, Kalita AJ, Dennis L, Henneco J, Tkachenko A, Sana H, Van Winckel H
Publication type: Article
Publication status: Published
Journal: Monthly Notices of the Royal Astronomical Society
Year: 2026
Pages: epub ahead of print
Online publication date: 06/08/2026
Acceptance date: 31/07/2026
Date deposited: 18/08/2026
ISSN (print): 0035-8711
ISSN (electronic): 1365-2966
Publisher: Oxford University Press
URL: https://academic.oup.com/mnras/advance-article/doi/10.1093/mnras/stag1493/8753687
DOI: 10.1093/mnras/stag1493
ePrints DOI: 10.57711/81m4-sf55
Data Access Statement: The TESS data used are publicly available via the MAST website: https://archive.stsci.edu/missions-and-data/ tess. The HERMES data are publicly available via the Mercator Observatory Archive website: https://www.mercator.iac.es/instruments/hermes/archive/. The GAIA data are publicly available via the Gaia website: https://gea.esac.esa.int/archive/, processed by the Gaia Data Processing and Analysis Consortium (DPAC; https://www.cosmos.esa.int/web/gaia/dpac/consortium). This research has made use of the following open-access soft ware packages: TLUSTY for the grids of synthetic spectra (Lanz & Hubeny 2003, 2007), LIGHTKURVE (https://lightkurve. github.io/lightkurve/), a PYTHON package for Kepler and TESS data analysis (Lightkurve Collaboration 2018), PERIOD04 (https://www.period04.net) for frequency analysis (Lenz & Breger 2005), as well as matplotlib (Hunter 2007), numpy (Harris et al. 2020), astropy (Astropy Collaboration et al. 2013b, 2018b, 2022), and scipy (Virtanen et al. 2020)
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