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More efficient multi-state selection
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@ -30,8 +30,22 @@ 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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integer :: k
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integer, save :: i_iter=0
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integer, parameter :: i_itermax = 3
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double precision, allocatable, save :: memo_variance(:,:), memo_pt2(:,:)
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dt = n_iter * selection_factor
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if (i_iter == 0) then
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allocate(memo_variance(N_st,i_itermax), memo_pt2(N_st,i_itermax))
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memo_pt2(:,:) = 1.d0
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memo_variance(:,:) = 1.d0
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endif
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i_iter = i_iter+1
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if (i_iter > i_itermax) then
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i_iter = 1
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endif
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dt = 4.d0
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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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@ -40,17 +54,23 @@ subroutine update_pt2_and_variance_weights(pt2, variance, norm, N_st)
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avg = sum(rpt2(1:N_st)) / dble(N_st)
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do k=1,N_st
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element = exp(dt*(rpt2(k)/avg -1.d0))
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element = min(1.2d0 , element)
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pt2_match_weight(k) *= element
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element = min(1.5d0 , element)
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element = max(0.5d0 , element)
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memo_pt2(k,i_iter) = element
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pt2_match_weight(k) = product(memo_pt2(k,:))
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enddo
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avg = sum(variance(1:N_st)) / dble(N_st)
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do k=1,N_st
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element = exp(dt*(variance(k)/avg -1.d0))
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element = min(1.2d0 , element)
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variance_match_weight(k) *= element
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element = min(1.5d0 , element)
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element = max(0.5d0 , element)
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memo_variance(k,i_iter) = element
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variance_match_weight(k) = product(memo_variance(k,:))
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enddo
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print *, '# PT2 weight ', real(pt2_match_weight(:),4)
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print *, '# var weight ', real(variance_match_weight(:),4)
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SOFT_TOUCH pt2_match_weight variance_match_weight
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end
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