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Starspots are thought to be regions of locally strong magnetic fields, similar to sunspots, and they can generate photometric brightness modulations. To deduce stellar and spot properties, such as spot emergence and decay rates, we implement computational code for starspot modeling. It is implemented with an adaptive parallel tempering algorithm and an importance sampling algorithm for parameter estimation and model selection in the Bayesian framework. For evaluating the performance of the code, we apply it to synthetic light curves produced with 3 spots. The light curves are specified in the spot parameters, such as the radii, intensities, latitudes, longitudes, and emergence/decay durations. The spots are circular with specified radii and intensities relative to the photosphere, and the stellar differential rotation coefficient is also included in the light curves. As a result, stellar and spot parameters are uniquely deduced. The number of spots is correctly determined: the 3-spot model is preferable because the model evidence is much greater than that of 2-spot models by orders of magnitude and more than that of 4-spot model by a more modest factor, whereas the light curves are produced to have 2 or 1 local minimum during one equatorial rotation period by adjusting the values of longitude. The spot emergence and decay rates can be estimated with error less than an order of magnitude, considering the difference of the number of spots.
General relativistic force-free electrodynamics is one possible plasma-limit employed to analyze energetic outflows in which strong magnetic fields are dominant over all inertial phenomena. The amazing images of black hole shadows from the galactic c
The study of the stability of massive gaseous disks around a star in a non-isolated context is not a trivial issue and becomes a more complicated task for disks hosted by binary systems. The role of self-gravity is thought to be significant, whenever
The use of Gaussian processes (GPs) as models for astronomical time series datasets has recently become almost ubiquitous, given their ease of use and flexibility. GPs excel in particular at marginalization over the stellar signal in cases where the
We present a forward-modeling framework using the Bayesian inference tool Starfish and cloudless Sonora-Bobcat model atmospheres to analyze low-resolution ($Rapprox80-250$) near-infrared ($1.0-2.5$ $mu$m) spectra of T dwarfs. Our approach infers effe
We describe the CRASH (Center for Radiative Shock Hydrodynamics) code, a block adaptive mesh code for multi-material radiation hydrodynamics. The implementation solves the radiation diffusion model with the gray or multigroup method and uses a flux l