Presentation #411.03 in the session Multi-messenger View of Supernovae, Gamma Ray Bursts, and Other Transients.
The highly energetic emission mechanisms from which Fast Radio Bursts (FRBs) originate have been the subject of intense investigation in recent years. Yet to be verified, many current theories predict association of multi-wavelength bursts with FRBs. Some efforts have been made in the search of such bursts, but none have resulted in positive detections. A prime consideration has been the fact that the prompt emission from FRBs is extremely short in duration, which effectively precludes multiwavelength followup via traditional target-of-opportunity campaigns. The optical counterparts of prompt emission from FRBs, Fast Optical Bursts (FOBs), would elucidate understanding on the progenitor and environment of such events. Here, we investigate a novel approach to the serendipitous detection of FOB’s through the fact that their seeing distorted images should look characteristically different than those of steady sources in a standard optical exposure of finite duration. In particular, for a steady source, the point spread function due to seeing involves an average over the distortions due to atmospheric turbulent structures that transit over the aperture while the image is being collected. In contrast, a fast optical flash of very short duration will exhibit distortions due to a much more limited patch of sky given by the projection of the primary aperture on the turbulent layers. As such, it will exhibit structure at higher spatial frequencies. We apply this idea to simulated observations with the Vera C. Rubin Observatory. We simulate FOB observations by tracing photons through an atmospheric model and a simulation model of the Rubin telescope. We compare these simulations to point-source star simulations of 15s duration, which is the nominal Rubin exposure time. A statistical power spectrum analysis is presented, showing relevant structural differences in the images that indicate the feasibility of distinguishing FOBs from point-source stars. We report the classification accuracy results of a Neural Network classifier on different FOBs. From this classifier, we derive constraints in duration-intensity parameter space for identifying FOBs in Rubin observations.