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Tuned selection

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This commit is contained in:
Anthony Scemama 2020-05-15 15:57:34 +02:00
parent 0776f88604
commit d4bebb07bc
1 changed files with 8 additions and 2 deletions
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10
src/cipsi/selection.irp.f
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@ -46,11 +46,11 @@ subroutine update_pt2_and_variance_weights(pt2, variance, norm, N_st)
i_iter = 1 i_iter = 1
endif endif
dt = 1.0d0 dt = 2.0d0
do k=1,N_st do k=1,N_st
! rPT2 ! rPT2
rpt2(k) = pt2(k)* (1.d0 + 1.d0/(1.d0 + norm(k))) rpt2(k) = pt2(k)/(1.d0 + norm(k))
enddo enddo
avg = sum(pt2(1:N_st)) / dble(N_st) - 1.d-32 ! Avoid future division by zero avg = sum(pt2(1:N_st)) / dble(N_st) - 1.d-32 ! Avoid future division by zero
@ -71,6 +71,12 @@ subroutine update_pt2_and_variance_weights(pt2, variance, norm, N_st)
variance_match_weight(k) *= product(memo_variance(k,:)) variance_match_weight(k) *= product(memo_variance(k,:))
enddo enddo
if (N_det < 100) then
! For tiny wave functions, weights are 1.d0
pt2_match_weight(:) = 1.d0
variance_match_weight(:) = 1.d0
endif
threshold_davidson_pt2 = min(1.d-6, & threshold_davidson_pt2 = min(1.d-6, &
max(threshold_davidson, 1.e-1 * PT2_relative_error * minval(abs(pt2(1:N_states)))) ) max(threshold_davidson, 1.e-1 * PT2_relative_error * minval(abs(pt2(1:N_states)))) )