Stellar Flares in Hiding: using hidden Markov models to find stellar flares in time series data from TESS

Oregon Convention Center 

Just as our own Sun emits solar flares, other stars emit stellar flares. Astrophysicists are interested in the number and energy distribution of stellar flares because this information can (1) test theories about stellar magnetic fields, and (2) be used to predict the habitability of the star's planetary system. Stellar flares appear in the time series data of a star's brightness as a quick rise followed by an exponential decay back to the star's approximately stationary state. The current methods to detect stellar flares rely on "3-sigma clipping": a Gaussian process (GP) models the stationary state of the time series, and points beyond three standard deviations are identified as flares. The disadvantage of this approach is that the dimmer (and therefore less energetic) flares will be missed. In this talk, I will describe our new method for discovering stellar flares in time series data of M-dwarf stars. Our novel Bayesian approach combines a 3-state Hidden Markov Model with a GP, and identifies flares through state-decoding. Simulations show this method finds the smaller flares missed by 3-sigma clipping, and gives a more accurate flare energy distribution estimate.