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Improved selection dynamic weights
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@ -32,7 +32,7 @@ subroutine update_pt2_and_variance_weights(pt2, variance, norm, N_st)
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double precision :: avg, rpt2(N_st), element, dt, x
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double precision :: avg, rpt2(N_st), element, dt, x
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integer :: k
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integer :: k
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integer, save :: i_iter=0
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integer, save :: i_iter=0
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integer, parameter :: i_itermax = 3
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integer, parameter :: i_itermax = 1
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double precision, allocatable, save :: memo_variance(:,:), memo_pt2(:,:)
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double precision, allocatable, save :: memo_variance(:,:), memo_pt2(:,:)
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if (i_iter == 0) then
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if (i_iter == 0) then
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@ -46,7 +46,7 @@ subroutine update_pt2_and_variance_weights(pt2, variance, norm, N_st)
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i_iter = 1
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i_iter = 1
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endif
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endif
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dt = 4.d0
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dt = 0.5d0
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do k=1,N_st
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do k=1,N_st
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rpt2(k) = pt2(k)/(1.d0 + norm(k))
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rpt2(k) = pt2(k)/(1.d0 + norm(k))
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@ -58,7 +58,7 @@ subroutine update_pt2_and_variance_weights(pt2, variance, norm, N_st)
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element = min(1.5d0 , element)
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element = min(1.5d0 , element)
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element = max(0.5d0 , element)
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element = max(0.5d0 , element)
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memo_pt2(k,i_iter) = element
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memo_pt2(k,i_iter) = element
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pt2_match_weight(k) = product(memo_pt2(k,:))
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pt2_match_weight(k) *= product(memo_pt2(k,:))
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enddo
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enddo
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avg = sum(variance(1:N_st)) / dble(N_st) + 1.d-32 ! Avoid future division by zero
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avg = sum(variance(1:N_st)) / dble(N_st) + 1.d-32 ! Avoid future division by zero
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@ -67,7 +67,7 @@ subroutine update_pt2_and_variance_weights(pt2, variance, norm, N_st)
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element = min(1.5d0 , element)
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element = min(1.5d0 , element)
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element = max(0.5d0 , element)
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element = max(0.5d0 , element)
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memo_variance(k,i_iter) = element
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memo_variance(k,i_iter) = element
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variance_match_weight(k) = product(memo_variance(k,:))
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variance_match_weight(k) *= product(memo_variance(k,:))
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enddo
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enddo
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threshold_davidson_pt2 = min(1.d-6, &
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threshold_davidson_pt2 = min(1.d-6, &
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