In the last decade a number of rapidly evolving transients have been discovered that are not easily explained by traditional supernovae models. We present optical and UV data on onee such object, SN 2018gep, that displayed a fast rise with a mostly featureless blue continuum around maximum light, and evolved to develop broad features more typical of a SN Ic-bl while retaining significant amounts of blue flux throughout its observations. The blue excess is most evident in its near-UV flux that is over 4 magnitudes brighter than other stripped envelope supernovae, but also visible in optical g−r colors at early times. Its fast rise time of t rise,V 6.2 ± 0.8 days puts it squarely in the emerging class of Fast Evolving Luminous Transients, or Fast Blue Optical Transients. With a peak absolute magnitude of M r = −19.49 ± 0.23 mag it is on the extreme end of both the rise time and peak magnitude distribution for SNe Ic-bl. Only one other SN Ic-bl has similar properties, iPTF16asu, for which less of the important early time and UV data have been obtained. We show that the objects SNe 2018gep and iPTF16asu have similar photometric and spectroscopic properties and that they overall share many similarities with both SNe Ic-bl and Fast Evolving Transients. We obtain IFU observations of the SN 2018gep host galaxy and derive a number of properties for it including M host = 7.8 +2.4 −1.2 × 10 7 M and a metallicity of log(O/H)+12 = 8.31 +0.07 −0.09 . We show that the derived host galaxy properties for both SN 2018gep and iPTF16asu are overall consistent with the SNe Ic-bl

It is believed that large-scale horseshoe-like brightness asymmetries found in dozens of transitional protoplanetary discs are caused by anticyclonic vortices. These vortices can play a key role in planet formation, as mm-sized dust -the building blocks of planets -can be accumulated inside them. Anticyclonic vortices are formed by the Rossby wave instability, which can be excited at the gap edges opened by a giant planet or at sharp viscosity transitions of accretionally inactive regions. It is known that vortices are prone to stretching and subsequent dissolution due to disc self-gravity for canonical disc masses in the isothermal approximation. To improve the hydrodynamic model of protoplanetary discs, we include the disc thermodynamics in our model. In this paper, we present our results on the evolution of the vortices formed at the outer edge of an accretionally inactive region (dead zone) assuming an ideal equation of state and taking PdV work, disc cooling in the β-approximation, and disc self-gravity into account. Thermodynamics affects the offset and the mode number (referring to the number of small vortices at the early phase) of the RWI excitation, as well as the strength, shape, and lifetime of the large-scale vortex formed through merging of the initial small vortices. We found that the inclusion of gas thermodynamics results in stronger, however decreased lifetime vortices. Our results suggest that a hypothetical vortex-aided planet formation scenario favours effectively cooling discs.

Recently, machine learning methods presented a viable solution for automated classification of image-based data in various research fields and business applications. Scientists require a fast and reliable solution to be able to handle the always growing enormous amount of data in astronomy. However, so far astronomers have been mainly classifying variable star light curves based on various pre-computed statistics and light curve parameters. In this work we use an image-based Convolutional Neural Network to classify the different types of variable stars. We used images of phase-folded light curves from the OGLE-III survey for training, validating and testing and used OGLE-IV survey as an independent data set for testing. After the training phase, our neural network was able to classify the different types between 80 and 99%, and 77-98% accuracy for OGLE-III and OGLE-IV, respectively.