Research Division Seminar
Mapping the Sun's upper photosphere with artificial neural networks
About the talk
Machine learning, atomic processes, magnetic fields, quantum mechanics, radiative transfer, scattering, stellar dynamics, turbulence, stars spots, stellar activity, Hinode, polarimeters, spectrographs, solar granulation, solar magnetic fields, solar photosphere, sunspots
iCalendar In this talk I'll present results from a recent paper in which we have developed a new analysis technique for solar spectra based on artificial neural networks. Our first test applications yielded some unexpected and interesting results. The fine-scale network of temperature enhancements in the quiet middle and upper photosphere have a reversed pattern. Hot pixels in the middle photosphere, possibly associated with small-scale magnetic elements, appear cool at higher levels (log(tau)=-3 and -4), and vice versa. We also find hot arcs on the limb side of magnetic pores, which we interpret as the first direct observational evidence of the "hot wall" effect. Hot walls are a prediction of theoretical models from the 1970s which had not been observed until now.