5.15.12. minimizer.sd

eminus.minimizer.sd(scf, Nit, cost=scf_step, grad=get_grad, condition=check_convergence, betat=3e-5, **kwargs)

Steepest descent minimization algorithm.

Parameters:

• scf – SCF object.

• Nit – Maximum number of SCF steps.

Keyword Arguments:

• cost – Function that will run every SCF step.

• grad – Function that calculates the respective gradient.

• condition – Function to check and log the convergence condition.

• betat – Step size.

• **kwargs – Throwaway arguments.

Returns:

Total energies per SCF cycle.