Ideas for finite_difference_grad.py about geometric HOT 4 OPEN

Thanks for the suggestions. I agree with many of the suggestions you made for finite_difference_grad.py, ideally it would share many of the command line arguments as the other "programs". A progress bar would be great (I never did get this to work). The embarrassingly parallel mode of finite_difference_grad.py (as well as the normal mode calculation in the optimizations) is currently handled using Work Queue. It creates a dependency but also enables one to run the gradient jobs on different physical machines.

Yes, I think it would be a good idea to use the optimization step as a finite difference step and compare it with the projection of the gradient in that direction. For large steps, a significant disagreement can be expected, but one should expect the agreement to improve as the steps become smaller assuming the gradient and energy are consistent. This could be done as part of the geometry optimization loop so that the user can be warned when there's energy/gradient inconsistency. I don't think additional steps to improve the numerical gradient quality are necessary, but it could be nice if implemented cleanly.

In fact it may be possible to use the energy change to "correct" the quantum chemical gradient, similar to how one updates the Hessian using BFGS, but I think that is a new research project.

from geometric.

The embarrassingly parallel mode of finite_difference_grad.py (as well as the normal mode calculation in the optimizations) is currently handled using Work Queue. It creates a dependency but also enables one to run the gradient jobs on different physical machines.

Does it allow to run N jobs on the same machine? I only have one for now :)

from geometric.

Yes. You simply run the finite_difference_grad.py and multiple copies of work_queue_worker on the same machine.

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Another practical consideration: I would like to evaluate quality of gradients on 9-molecule cluster which we've discussed in another issue, however that system contains 180 atoms so it would require huge amount of resources to compute. However, evaluation of 3 points for a single step vector could be done quickly.

from geometric.