The energy minimizer (adapted from MR) tries to find force zeros. However when the minimizer tries to take a large step, we need to take a smaller step (backtrack). Two strategies are currently applied for backtracking: (i) Decimation - new step is 1/10 of previous step, (ii) AH - linearizes force and solves for the zero of the straight line.
Decimation is significantly slower than AH because it uses no information about the magnitude of the forces & hence tries a large number of moves whereas AH zeroes onto the correct move very quicky. Since decimation samples a large number of points of the search space, most of which are far from the starting point, the chance of it finding a minimum far away from the staring point is very high.
The latter case has been observed in indentation runs where decimation frequently shows a load drop before AH, especially when stepping by 1e-6 & sometimes when we step by 1e-5 too.
Problems/Observations with indentation runs:
(i) The biggest problem is that 4x-quadruple nucleates along 2 modes. Despite shifting the indenter horizontally, the problem persists. The best I was able to do was with AH, where upto steps of 1e-4, I was able to obtain nucleation along a single mode. However I still got a featureless velocity field.
ASIDE: An MD run, with fix viscous on, showed only one nucleation mode. The indeter depth was ~1 particle spacing lower than energy minimization.
(ii) I just observed that one gets a featureless velocity field in 2xquad if the state had been reached with decim but we try to define velocity with AH (or vice versa, can't recall). This is very peculiar and should be looked into.
(iii) All of the other systems gave defect-incipient velocity vector field that allowed computeCrossStrain.py to do its job 'fromScratch', although most velocity fields weren't 'clean' - especiallly those from 'decim' (probably because of its tendency to jump far).
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