A framework for interpreting fast radio transients search experiments: application to the V-FASTR experiment

TL;DR

This paper introduces a comprehensive framework for interpreting fast radio transient search experiments, enabling the combination of multiple datasets and accounting for various observational effects, demonstrated through the V-FASTR experiment and predictions for SKA.

Contribution

It presents a novel probabilistic framework for combining datasets and constraining transient event rates, incorporating beam shape, frequency, scattering, and detection efficiency effects.

Findings

V-FASTR can probe key parameter space for fast radio transients.

Combining V-FASTR and ATA Fly's Eye results demonstrates their complementarity.

Framework enables predictions for SKA Phase I transient searches.

Abstract

We define a framework for determining constraints on the detection rate of fast transient events from a population of underlying sources, with a view to incorporating beam shape, frequency effects, scattering effects, and detection efficiency into the metric. We then demonstrate a method for combining independent datasets into a single event rate constraint diagram, using a probabilistic approach to the limits on parameter space. We apply this new framework to present the latest results from the V-FASTR experiment, a commensal fast transients search using the Very Long Baseline Array (VLBA). In the 20 cm band, V-FASTR now has the ability to probe the regions of parameter space of importance for the observed Lorimer and Keane fast radio transient candidates, by combining the information from observations with differing bandwidths, and properly accounting for the source dispersion measure, VLBA antenna beam shape, experiment time sampling, and stochastic nature of events. We then apply the framework to combine the results of the V-FASTR and ATA Fly's Eye experiments, demonstrating their complementarity. Expectations for fast transients experiments for the SKA Phase I dish array are then computed, and the impact of large differential bandwidths is discussed.