Blocked-Davidson algorithm: Difference between revisions

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\left \{ \psi^1_k \, / \,  g^1_k =  \left (1- \sum_{n=1}^{N_{\rm bands}} | \psi_n \rangle \langle\psi_n | {\bf S} \right) {\bf K} \left ({\bf H} -  \epsilon_{\rm app} {\bf S} \right ) \psi^1_k \, | \, k=1,..,n_1 \right \}.
\left \{ \psi^1_k \, / \,  g^1_k =  \left (1- \sum_{n=1}^{N_{\rm bands}} | \psi_n \rangle \langle\psi_n | {\bf S} \right) {\bf K} \left ({\bf H} -  \epsilon_{\rm app} {\bf S} \right ) \psi^1_k \, | \, k=1,..,n_1 \right \}.
</math>
</math>
* Rayleigh-Ritz optimization ("subspace rotation") within the <math>2n_1</math> dimensional space spanned by <math>\{\psi^1/g^1\}</math>, to determine the <math>n_1</math> lowest eigenvectors:
* Rayleigh-Ritz optimization ("subspace rotation") within the <math>2n_1</math>-dimensional space spanned by <math>\{\psi^1/g^1\}</math>, to determine the <math>n_1</math> lowest eigenvectors:
:<math>{\rm diag}\{\psi^1/g^1\} \Rightarrow \{ \psi^2_k| k=1,..,n_1\}</math>
:<math>{\rm diag}\{\psi^1/g^1\} \Rightarrow \{ \psi^2_k| k=1,..,n_1\}</math>
* Extend the subspace with residuals of <math>\{\psi^2\}</math>:
* Extend the subspace with the residuals of <math>\{\psi^2\}</math>:
:<math>
:<math>
\left \{ \psi^2_k \,/ \,  g^1_k \, / \, g^2_k =  \left (1- \sum_{n=1}^{N_{\rm bands}} | \psi_n \rangle \langle\psi_n | {\bf S} \right ) {\bf K} \left ({\bf H} -  \epsilon_{\rm app}  {\bf S} \right)  \psi^2_k  \, | \, k=1,..,n_1 \right \}.
\left \{ \psi^2_k \,/ \,  g^1_k \, / \, g^2_k =  \left (1- \sum_{n=1}^{N_{\rm bands}} | \psi_n \rangle \langle\psi_n | {\bf S} \right ) {\bf K} \left ({\bf H} -  \epsilon_{\rm app}  {\bf S} \right)  \psi^2_k  \, | \, k=1,..,n_1 \right \}.
</math>
</math>
* Rayleigh-Ritz optimization ("subspace rotation") within the <math>3n_1</math> dimensional space spanned by <math>\{\psi^1/g^1/g^2\}</math>:
* Rayleigh-Ritz optimization ("subspace rotation") within the <math>3n_1</math>-dimensional space spanned by <math>\{\psi^1/g^1/g^2\}</math>:
:<math>{\rm diag}\{\psi^1/g^1/g^2\} \Rightarrow \{ \psi^3_k| k=1,..,n_1\}</math>
:<math>{\rm diag}\{\psi^1/g^1/g^2\} \Rightarrow \{ \psi^3_k| k=1,..,n_1\}</math>
* 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:
* 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:
:<math>{\rm diag}\{\psi^1/g^1/g^2/../g^{d-1}\}\Rightarrow \{ \psi^d_k| k=1,..,n_1\}</math>
:<math>{\rm diag}\{\psi^1/g^1/g^2/../g^{d-1}\}\Rightarrow \{ \psi^d_k| k=1,..,n_1\}</math>
: Per default {{VASP}} will not iterate deeper than <math>d=4</math>, though it may break off even sooner when certain criteria that measure the convergence of the orbitals have been met.
: Per default {{VASP}} will not iterate deeper than <math>d=4</math>, 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 in 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>.
* Continue with the next block <math>\{ \psi^1_k| k=n_1+1,..,2 n_1\}</math>.
* After each band has been optimized a Rayleigh-Ritz optimization in the complete subspace <math>\{ \phi_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.


This method is approximately a factor of 1.5-2 slower than RMM-DIIS, but always stable. It is available in parallel for any data distribution.
This method is approximately a factor of 1.5-2 slower than [[RMM-DIIS]], but more robust.

Revision as of 19:03, 19 October 2023

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

  • 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:
.
  • Continue with the next block .
  • After all orbitals have been optimized, a Rayleigh-Ritz optimization in the complete subspace is performed.

This method is approximately a factor of 1.5-2 slower than RMM-DIIS, but more robust.