Having defined defects as above (counting both point and fluctuational defects) we would like to compute an appropriate figure of merit (FOM) for a given BCP dot array, which measures how desirable that BCP array would be if used for bit patterned media. Although a raw average of the defect density is informative and simple to measure, it does not tell us how the defects are distributed in space. For instance, are they all located on grain boundaries or are they uniformly distributed throughout? As such, we define the metric of local defect distance, which is simply the minimum distance between a BCP dot and a defect (normalized by BCP pitch). Shown in Figure are the local defect distance maps for each SVA condition tested. It is worth noting that these local defect distance maps are simply the Euclidean distance transform of the defect maps (Figure ). In contrast to the 𝑅 " maps, the local defect distance maps show that, from patterned bit media perspective, better BCP arrays can be made from films with initial thicknesses of 28 nm, compared to 33 nm (i.e. there are much larger regions that do not contain any defects). This metric of defect distance can be directly related to yield and size of bit-patterned media devices, where an average of the local defect distance of the entire BCP array gives a measure of how large a device could be fabricated without any defects. Specifically, the effective defect distance is defined as the 20% percentile of local defect distance for a given BCP array (this distance would equal the device size that would have an ~80% yield, meaning no defects for 80% of devices). A map of the effective defect distance (as a function of SVA conditions) is shown in Figure , which clearly identifies a narrow region of optimal annealing conditions centered around an initial thickness of ~30 nm and swelling degree of ~2.0.