In Figure we can see the effect of different sampling frequencies. While the overall pattern remains the same, they differ in a few ways that are useful for overall analysis of a trajectory. For example, the same critical points of formation beginning at about 40.0 µs and rupturing at 150 µs exist in all diagrams. While the lines of critical behaviour become clearer with more samples, the fact that they exist at all timesteps reinforces their importance. At a very small timestep, short-lived rings (or absences of rings) can be missed out. A short timestep will count a superset of the rings identified using a large timestep, but include many more rings with lifespans less than the window size ∆t. This also means that repair phenomena can be missed if the timestep is too short compared to the timescale of repair. This is especially obvious if we highlight the number of times a given ring is repaired against the timescale, as is shown in Figure . These show that if the timescale is increased, repair phenomena can be missed entirely; this manifests as the graphs trailing off to show on average one birth per ring and that they are alive continuously over their lifespan for long sampling timescales. However, at lower sampling timescales the repair phenomena become clear as each ring is repeatedly reborn and is only alive for a fraction of its total lifespan. This does not plateau at short timespans, indicating that there are possibly infinitely many microscopic damage and repair phenomena before a ring is destroyed for good as a consequence of the thermal motion of the connecting sites.