Researchers from the Center for Astrophysics | Harvard & Smithsonian, including Qiyuan Wang, Giovanni Motta, Genaro Sucarrat, and Vinay L. Kashyap, have developed a novel method to analyze time series data, with significant implications for understanding stellar activity and, by extension, energy production and space weather impacts on Earth’s energy infrastructure.
The team’s research, published in the Astrophysical Journal, focuses on detecting stellar flares—sudden, intense bursts of radiation from stars—amidst complex background data. The method they’ve developed is particularly adept at identifying these flares even when the baseline stellar light curves exhibit irregular oscillations and stochastic volatility, much like the fluctuations seen in financial time series.
The researchers first remove the underlying non-stochastic trend using a time-varying amplitude harmonic model. This step is crucial for isolating the stochastic component of the light curves, which they then model as an ARMA+GARCH process—a statistical approach commonly used in financial time series analysis. This analogy allows the team to detect and characterize impulsive flares as large deviations that are inconsistent with the correlation structure in the light curve.
The method was applied to light curves from three exemplar stars observed with the Transiting Exoplanet Survey Satellite (TESS). The researchers detected a significant number of flares, with rates ranging from approximately 0.4 to 8.5 flares per day, depending on the star and the detection threshold. Notably, they were able to detect flares with amplitudes as low as 0.007% of the bolometric luminosity.
The team also modeled the distributions of flare energies and peak fluxes as power-laws, finding that the solar-like star in their sample exhibited values similar to those observed on the Sun. For the less and highly active low-mass stars, the power-law indices were found to be greater than and less than 2, respectively.
The practical applications of this research for the energy sector are manifold. Understanding stellar flares and their patterns is crucial for predicting space weather events, which can have significant impacts on Earth’s energy infrastructure, including power grids and satellite communications. By improving our ability to detect and characterize stellar flares, this research contributes to the broader effort to mitigate the risks posed by space weather to our energy systems.
This article is based on research available at arXiv.