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Register a new userSimbol-X capability of detecting the non-thermal emission of stellar flares
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Authors
C. Argiroffi
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We investigate the capability of detecting, with Simbol-X, non-thermal emission during stellar flares, and distinguishing it from hot thermal emission. We find that flare non-thermal emission is detectable when at least ~20 cts are detected with the CZT detector in the 20-80 keV band. Therefore Simbol-X will detect the non-thermal emission from some of the X-ray brightest nearby stars, whether the thermal vs. non-thermal relation, derived for solar flares, holds.
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The detection of red/blue-shifted iron lines in the spectra of astronomical X-ray sources is of great importance, as it allows to trace the environment around compact objects, like black holes in AGNs. We report on extensive simulations to test the Simbol-X capability of detecting such spectral features, focusing on the low energy detector (0.5-30 keV).
Deep radio observations of galaxy clusters have revealed the existence of diffuse radio sources (halos and relics) related to the presence of relativistic electrons and weak magnetic fields in the intracluster volume. I will outline our current knowledge about the presence and properties of this non-thermal cluster component. Despite the recent progress made in observational and theoretical studies of the non-thermal emission in galaxy clusters, a number of open questions about its origin and its effects on the thermo-dynamical evolution of galaxy clusters need to be answered. I will show the importance of combining galaxy cluster observations by new-generation instruments such as LOFAR and Simbol-X. A deeper knowledge of the non-thermal cluster component, together with statistical studies of radio halos and relics, will allow to test the current cluster formation scenario and to better constrain the physics of large scale structure evolution.
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We present a Bayesian-odds-ratio-based algorithm for detecting stellar flares in light curve data. We assume flares are described by a model in which there is a rapid rise with a half-Gaussian profile, followed by an exponential decay. Our signal model also contains a polynomial background model. This is required to fit underlying light curve variations that are expected in the data, which could otherwise partially mimic a flare. We characterise the false alarm probability and efficiency of this method and compare it with a simpler thresholding method based on that used in Walkowicz et al (2011). We find our method has a significant increase in detection efficiency for low signal-to-noise ratio (S/N) flares. For a conservative false alarm probability our method can detect 95% of flares with S/N less than ~20, as compared to S/N of ~25 for the simpler method. As an example we have applied our method to a selection of stars in Kepler Quarter 1 data. The method finds 687 flaring stars with a total of 1873 flares after vetos have been applied. For these flares we have characterised their durations and and signal-to-noise ratios.
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