anchor.diff:  
       end subroutine neel_trial_state
   
  -    ! [review] - JSS: what about original, non-symmetric algorithm?
  -    ! [review] - JSS: is the user prevented from running such (unsupported)
  -    ! [review] - JSS: calculations via a sanity check somewhere?
  -
       subroutine dmqmc_int_pic_free_importance_sampling(sys, cdet, connection, trial_func, hmatel)
   
           ! Apply a transformation to the Hamiltonian matrix element by
           ! reducing the probability of spawning to higher excitation levels
           ! between the two ends of the DMQMC bitstring. The exact trial function
           ! used is specified by the users upon input, and stored in the vector
  -        ! accumulated_probs.
  +        ! accumulated_probs. Here we apply the transformation to the interaction
  +        ! picture Hamiltonian, where H^0 = T.
  +
   
           ! This is a wrapper function for using importance sampling with the symmetric version
           ! of the ip-dmqmc algorithm, which also requires the Hamiltonian matrix element to be reweighted.
  
positive.code:         !        and the child determinant, on which progeny are spawned.
          !    trial_func: importance sampling weights.
          ! In/Out:
          ! [review] - JSS:  see comments in dmqmc_int_pic_hf_importance_sampling
          !    hmatel: on input, untransformed matrix element connecting two spin
          !        functions (kets).  On output, transformed matrix element,
          !        \Psi^T(cdet%f,cdet%f2) H_{ij} 1/\Psi(f_new,cdet%f2).
          !        The factors which the Hamiltonian are multiplied by depend
          !        on the level which we come from, and go to, and so depend on
          !        the two ends of the bitstring we spawn from, and the new
  
negative.code:         ! reducing the probability of spawning to higher excitation levels
          ! between the two ends of the DMQMC bitstring. The exact trial function
          ! used is specified by the users upon input, and stored in the vector
          ! accumulated_probs. Here we apply the transformation to the interaction
          ! picture Hamiltonian, where H^0 = H^HF.
  
          ! This is a wrapper function for using importance sampling with the symmetric version
          ! of the ip-dmqmc algorithm, which also requires the hamiltonian matrix element to be reweighted.
  