Enhancing SDO/HMI images using deep learning

The Helioseismic and Magnetic Imager (HMI) provides continuum images and magnetograms with a cadence better than one per minute. It has been continuously observing the Sun 24 hours a day for the past 7 years. The obvious trade-off between full disk observations and spatial resolution makes HMI not enough to analyze the smallest-scale events in the solar atmosphere. Our aim is to develop a new method to enhance HMI data, simultaneously deconvolving and super-resolving images and magnetograms. The resulting images will mimic observations with a diffraction-limited telescope twice the diameter of HMI. Our method, which we call Enhance, is based on two deep fully convolutional neural networks that input patches of HMI observations and output deconvolved and super-resolved data. The neural networks are trained on synthetic data obtained from simulations of the emergence of solar active regions. We have obtained deconvolved and supper-resolved HMI images. To solve this ill-defined problem with infinite solutions we have used a neural network approach to add prior information from the simulations. We test Enhance against Hinode data that has been degraded to a 28 cm diameter telescope showing very good consistency. The code is open source.Comment: 13 pages, 10 figures. Accepted for publication in Astronomy & Astrophysic

How does breakup influence the total fusion of 6,7^{6,7}Li at the Coulomb barrier?

Total (complete + incomplete) fusion excitation functions of $^{6,7}$Li on $^{59}$Co and $^{209}$Bi targets around the Coulomb barrier are obtained using a new continuum discretized coupled channel (CDCC) method of calculating fusion. The relative importance of breakup and bound-state structure effects on total fusion is particularly investigated. The effect of breakup on fusion can be observed in the total fusion excitation function. The breakup enhances the total fusion at energies just around the barrier, whereas it hardly affects the total fusion at energies well above the barrier. The difference between the experimental total fusion cross sections for $^{6,7}$Li on $^{59}$Co is notably caused by breakup, but this is not the case for the $^{209}$Bi target.Comment: 9 pages, 9 figures, Submitted to Phys. Rev.

On the use of the Fourier Transform to determine the projected rotational velocity of line-profile variable B stars

The Fourier Transform method is a popular tool to derive the rotational velocities of stars from their spectral line profiles. However, its domain of validity does not include line-profile variables with time-dependent profiles. We investigate the performance of the method for such cases, by interpreting the line-profile variations of spotted B stars, and of pulsating B tars, as if their spectral lines were caused by uniform surface rotation along with macroturbulence. We perform time-series analysis and harmonic least-squares fitting of various line diagnostics and of the outcome of several implementations of the Fourier Transform method. We find that the projected rotational velocities derived from the Fourier Transform vary appreciably during the pulsation cycle whenever the pulsational and rotational velocity fields are of similar magnitude. The macroturbulent velocities derived while ignoring the pulsations can vary with tens of km/s during the pulsation cycle. The temporal behaviour of the deduced rotational and macroturbulent velocities are in antiphase with each other. The rotational velocity is in phase with the second moment of the line profiles. The application of the Fourier method to stars with considerable pulsational line broadening may lead to an appreciable spread in the values of the rotation velocity, and, by implication, of the deduced value of the macroturbulence. These two quantities should therefore not be derived from single snapshot spectra if the aim is to use them as a solid diagnostic for the evaluation of stellar evolution models of slow to moderate rotators.Comment: 13 pages, 9 figures, accepted for publication in Astronomy & Astrophysic

Self-organized evolution in socio-economic environments

We propose a general scenario to analyze social and economic changes in modern environments. We illustrate the ideas with a model that incorporating the main trends is simple enough to extract analytical results and, at the same time, sufficiently complex to display a rich dynamic behavior. Our study shows that there exists a macroscopic observable that is maximized in a regime where the system is critical, in the sense that the distribution of events follow power-laws. Computer simulations show that, in addition, the system always self-organizes to achieve the optimal performance in the stationary state.Comment: 4 pages RevTeX; needs epsf.sty and rotate.sty; submitted to Phys Rev Let