Localizing Stellar Activity on Low Mass Stars with the Transiting Exoplanet Survey Satellite 2. Sample Demographics 1. Stellar Activity Julie Moquin1,2, Jordan Ealy1,3, Joshua Schlieder1 1Goddard Space Flight Center, 2Rice University, 3University of Maryland College Park Fig 1. The above ﬁgure depicts how a ﬂare is created through magnetic ﬁeld reconnection. ●Low-mass stars often have high ﬂaring rates ●Caused by a sudden magnetic reconnection ●Usually associated with star spots [Ikuta et al. 2023] ●Spot modulation is caused by a decrease in optical ﬂux from an increase in star spot coverage. ●BANYAN Moving Group Stars [Gagné et al. 2018] ○Stars from β Pictoris Moving Group (βPMG), AB Doradus Moving Group (ABDMG), Tucana-Horologium Association (THA), Columba Association (COL), Carina Moving Group (CAR) ●Sample optimization removed the ﬁeld stars as they do not have detectable spot modulation. ●We used Lightkurve [Lightkurve Collaboration 2018] to examine the light curves for possible contamination. Credit: NASA/ESA/G. Baco 3. Data Analysis Phase Folding the Light Curves Fig 5. Phase-folded light curve with an oﬀset. Using an oﬀset makes it easier to see where the ﬂares are located in the phase-folded graph. Fig 4. (a) a TESS light curve. (b) The same light curve, but phase-folded. ●To phase-fold a light curve, the light curve is folded based on the star's rotation rate which we estimate using a Lomb-Scargle periodogram ●Phase-folding aids with visualizing in which area of the period the ﬂares are located Localizing Stellar Activity on Low-Mass Stars with the Transiting Exoplanet Survey Satellite Julie Moquin Jordan Ealy Joshua Schlieder Credit: NASA/ESA/G. Bacon (STScI) βPMG (~24 Myr§) ABDMG (~149 Myr§) THA (~45 Myr§) COL (~42 Myr§) CAR (~45 Myr§) 8 4 4 11 1 33.7% 17.1% 27.1% 1.0% 21.1% Fig 3. The outer donut chart depicts the percentage of light curves used from each moving group. The inner donut chart depicts the number of sources used from each moving group. The color blocks are diﬀerent shapes as some stars had multiple sectors of observation. The sectors were treated individually to maintain observation integrity. ●Trends in ﬂare rates and spot modulation can provide a means to “localize” on the rotation phase where ﬂares occur more frequently and whether they are associated with active regions (ie star spots). We selected our sample to include young stars. Fig 2. Spot modulation is seen in light curves as the dips in ﬂux. For young stars, other sources of variability can cause aperiodic brightness changes and lead to complex, non-sinusoidal morphologies. The zoom in shows the morphology of a ﬂare and the spot modulation. Future Work Localizing the Flares ●Inﬂection Point Sectioning ●Rigorous Statistics on Flare Distribution Results ●Continuum localization ●To validate our methods, we did an initial survey on 44 light curves with consistent, sinusoidal spot modulation. We plotted the start location of ﬂares along the rotation phase. The phase-folded light curves were co-aligned in phase space using their minima. We used AltaiPony [Ilin et al. 2021] to detect the ﬂares on all the light curves. A ﬂare is detected if there is enough data 3σ above the midline. The midline is found by detrending the light curve, which removes the periodic signal from the light curve. Identifying the Flares Fig 6. The ﬂares are highlighted in blue. This is useful for making sure that all ﬂares are identiﬁed properly and allows for localization analysis by eye. Scan me for abstract, contact information, and references! Fig 7. All panels are aligned in phase and colored by eﬀective temperature of the ﬂaring star. (a) Phase-folded light curves. Oﬀset peaks show varied spot coverage. (b) Distribution of the ﬂare start times. (c) Cumulative histogram of the ﬂare density with a kernel density estimate line. We see a higher density of ﬂares closer to the minimum. 1 2 3 4 5 (a) (b) 6 ●This histogram hints that there are more ﬂares around the minima of