Blocked-Davidson algorithm: Difference between revisions

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* When the iteration is finished, store the optimized block of orbitals back into the set:
* When the iteration is finished, store the optimized block of orbitals back into the set:
:<math>\{ \psi^d_k| k=1,..,n_1\} \Rightarrow \{ \psi_k| k=1,..,N_{\rm bands}\}</math>.
:<math>\{ \psi^d_k| k=1,..,n_1\} \Rightarrow \{ \psi_k| k=1,..,N_{\rm bands}\}</math>.
* Continue with the next block <math>\{ \psi^1_k| k=n_1+1,..,2 n_1\}</math>.
* Move on to the next block <math>\{ \psi^1_k| k=n_1+1,..,2 n_1\}</math>.
* After all orbitals have been optimized, a Rayleigh-Ritz optimization in the complete subspace <math>\{ \psi_k| k=1,..,N_{\rm bands}\}</math> is performed.
* After all orbitals have been optimized, a Rayleigh-Ritz optimization in the complete subspace <math>\{ \psi_k| k=1,..,N_{\rm bands}\}</math> is performed.



Revision as of 19:16, 19 October 2023

The workflow of the blocked-Davidson iterative matrix diagonalization scheme implemented in VASP is as follows:[1][2]

  • Take a subset (block) of orbitals out of the total set of NBANDS orbitals:
.
  • Extend the subspace spanned by by adding the preconditioned residual vectors of :
  • Rayleigh-Ritz optimization ("subspace rotation") within the -dimensional space spanned by , to determine the lowest eigenvectors:
  • Extend the subspace with the residuals of :
  • Rayleigh-Ritz optimization ("subspace rotation") within the -dimensional space spanned by :
  • If need be the subspace may be extended by repetition of this cycle of adding residual vectors and Rayleigh-Ritz optimization of the resulting subspace:
Per default VASP will not iterate deeper than , though it may break off even sooner when certain criteria that measure the convergence of the orbitals have been met.
  • When the iteration is finished, store the optimized block of orbitals back into the set:
.
  • Move on to the next block .
  • After all orbitals have been optimized, a Rayleigh-Ritz optimization in the complete subspace is performed.

The blocked-Davidson algorithm is approximately a factor of 1.5-2 slower than the RMM-DIIS, but more robust.

References