FULLCNV — Fully converge conjugate gradient at each SCF cycle.

FULLCNV

PSOLVE=CGDMS and PSOLVE=QNDMS solve for the density matrix using a congugate gradient (CG) procedure. Typically, a CG procedure iterates until all of its convergence criteria are satisfied. For CGDMS and QNDMS, it is unnecessary to fully converge things at every single SCF, since we only need the density to be converged at the final SCF step. This leads to the notion of progressive convergence, where we limit the CG to only 4 steps. In general, progressive convergence will greatly reduce the number of CG iterations without increasing (or only marginally increasing) the total number of SCF iterations and so is the default behavior for these methods. FULLCNV forces the use of full convergence instead of progressive convergence.

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