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mirror of https://github.com/QuantumPackage/qp2.git synced 2024-12-08 20:53:31 +01:00

Improved weights

This commit is contained in:
Anthony Scemama 2019-06-05 15:07:36 +02:00
parent 04ca07a540
commit 453cfa0b65

View File

@ -31,7 +31,7 @@ subroutine update_pt2_and_variance_weights(pt2, variance, norm, N_st)
double precision :: avg, rpt2(N_st), element, dt, x
integer :: k
dt = 2.d0 * selection_factor
dt = n_iter * selection_factor
do k=1,N_st
rpt2(k) = pt2(k)/(1.d0 + norm(k))
@ -40,7 +40,6 @@ subroutine update_pt2_and_variance_weights(pt2, variance, norm, N_st)
avg = sum(rpt2(1:N_st)) / dble(N_st)
do k=1,N_st
element = exp(dt*(rpt2(k)/avg -1.d0))
element = max(0.8d0, element)
element = min(1.2d0 , element)
pt2_match_weight(k) *= element
enddo
@ -48,12 +47,9 @@ subroutine update_pt2_and_variance_weights(pt2, variance, norm, N_st)
avg = sum(variance(1:N_st)) / dble(N_st)
do k=1,N_st
element = exp(dt*(variance(k)/avg -1.d0))
element = max(0.8d0, element)
element = min(1.2d0 , element)
variance_match_weight(k) *= element
enddo
print *, "rPT2-weights:", real(pt2_match_weight(:),4)
print *, "Variance-weights:", real(variance_match_weight(:),4)
SOFT_TOUCH pt2_match_weight variance_match_weight
end
@ -67,21 +63,27 @@ BEGIN_PROVIDER [ double precision, selection_weight, (N_states) ]
select case (weight_selection)
case (0)
print *, 'Using input weights in selection'
selection_weight(1:N_states) = state_average_weight(1:N_states)
case (1)
print *, 'Using 1/c_max^2 weight in selection'
selection_weight(1:N_states) = c0_weight(1:N_states)
case (2)
print *, 'Using pt2-matching weight in selection'
selection_weight(1:N_states) = c0_weight(1:N_states) * pt2_match_weight(1:N_states)
case (3)
print *, 'Using variance-matching weight in selection'
selection_weight(1:N_states) = c0_weight(1:N_states) * variance_match_weight(1:N_states)
case (4)
print *, 'Using variance- and pt2-matching weights in selection'
selection_weight(1:N_states) = c0_weight(1:N_states) * variance_match_weight(1:N_states) * pt2_match_weight(1:N_states)
case (5)
print *, 'Using variance-matching weight in selection'
selection_weight(1:N_states) = c0_weight(1:N_states) * variance_match_weight(1:N_states)
end select