The CubeSpec space mission

Context. Massive stars play a central role in astrophysics, yet their internal structure remains poorly constrained due to uncertainties regarding their core masses, internal rotation, and chemical mixing. Through pulsation mode identification, asteroseismology offers a unique window into stellar interiors. However, current spectroscopic ground-based observational campaigns suffer from diurnal and weather-induced gaps, and space missions historically assembled time series through photometry. A complementary strategy that delivers the necessary frequency resolution and high cadence is provided by spectroscopy, which is highly beneficial for unambiguous mode identification in β Cephei stars. CubeSpec is an ESA in-orbit demonstrator 12U CubeSat with a compact and high-resolution échelle spectrograph, dedicated to delivering space-based high-cadence high-resolution spectroscopy, which is used to identify mode geometries of β Cephei pulsators. Aims. We investigated observational scenarios with various sampling pulsation cycles over the duration of the CubeSpec mission to ensure the retrievability of pulsation frequencies and unambiguously identify pulsation modes in massive stars, specifically from high-cadence high-resolution spectroscopic time series. Methods. We simulated time series of line profile variations by combining atmosphere models with pulsation kernels. These synthetic time series include realistic instrumental responses, cadence variations, and noise characteristics. We assessed the retrievability of pulsation frequencies and mode geometries with two analysis techniques for different observational scenarios and various mode configurations, sampling cadence, mission time span, and data quality. Results. Our simulations show that CubeSpec’s spectroscopic time series allow for reliable frequency extraction and mode identification across various pulsational and orbital scenarios, according to established science requirements of the mission. Especially, we identify mode amplitude and observational cadence as the key factors governing both the successful frequency retrieval and the critical conditions breaking it, thereby highlighting the need for modelling with a realistic cadence in the future.