Hi @stefanocapaldi,
Welcome to the forum! The noise model (sigma) plot shows us an estimate of the non-structure noise present in the images, as a function of spatial frequency. It is estimated via computing the “residual” in each image – this is the squared difference between the raw data, and the CTF-corrupted projection of the density. If you are familiar with Scheres, 2012, it is very similar to equation (4) for estimation of sigma.
The sigma we compute & plot is this squared difference, averaged over all images, and also averaged over all frequencies at a given resolution shell (we call this a “symmetric” or “circularly symmetric” noise model). The plot for error shows this quantity before circularly-averaging, but the differences between sigma and error are usually insignificant.
Best,
Michael