anchor.diff:  
           min_cluster_size = 0
           selection_data%nD0_select = 0 ! instead of this number of deterministic selections, these are chosen stochastically
  -        selection_data%nstochastic_clusters = nattempts!*10**3
  +        selection_data%nstochastic_clusters = nattempts*100
           selection_data%nsingle_excitors = 0
   
           selection_data%nclusters = selection_data%nD0_select + selection_data%nsingle_excitors &
  
positive.code:                                             selection_data%nstochastic_clusters, D0_normalisation, qmc_in%initiator_pop, D0_pos, &
                                              cumulative_abs_real_pops, tot_abs_real_pop, min_cluster_size, max_cluster_size, &
                                              logging_info, contrib(it)%cdet, contrib(it)%cluster, qs%excit_gen_data)
                      !print*, 'selected',  contrib(it)%cdet%f
  
                      if (uccmc_in%variational_energy .and. .not. all(contrib(it)%cdet%f==0) .and. contrib(it)%cluster%excitation_level <= qs%ref%ex_level)  then
                         state = contrib(it)%cdet%f 
                         call binary_search(time_avg_psip_list_ci_states, state, 1, nstates_ci, hit, pos)
  
negative.code:                 proj_energy_cycle = cmplx(0.0, 0.0, p)
                  D0_population_cycle = cmplx(0.0, 0.0, p)
                  D0_population_ucc_cycle = 0.0_p
                  !$omp do schedule(dynamic,200) reduction(+:D0_population_cycle,proj_energy_cycle, D0_population_ucc_cycle, nattempts_spawn,ndeath)
                  do iattempt = 1, selection_data%nclusters
                      ! For OpenMP scalability, have this test inside a single loop rather
  