Collective oscillations and patterns of synchrony have long fascinated researchers in the applied sciences, particularly due to their far-reaching importance in chemistry, physics, and biology. The Kuramoto model has emerged as a prototypical mathematical equation to understand synchronization in coupled oscillators, allowing one to study the effect of different frequency distributions and connection networks between oscillators. In this work we provide a framework for determining both the emergence and the persistence of synchronous solutions to Kuramoto models on large random networks and with random frequencies. This is achieved by appealing the theory of graphons to analyze a mean-field model coming in the form of an infinite oscillator limit which provides a single master equation for studying random Kuramoto models. We show that bifurcations to synchrony and hyperbolic synchrony patterns in the mean-field model can also be found in related random Kuramoto networks for large numbers of oscillators. We further provide a detailed application of our results to oscillators arranged on Erdos--R\'enyi random networks, for which we further identify that not all bifurcations to synchrony emerge through simple co-dimension one bifurcations.
Bramburger et al. (Mon,) studied this question.