Firstly, it is possible that the set of molecular features is not descriptive enough to reproduce the target structures to high enough accuracy, that is, the system could obtain very low loss values while still not reaching low root mean squared distances (RMSD) to the target structure. Secondly, it is possible that U GP is not smooth with respect to X GP and A GP , and that the particles get caught in local energy minima. To address both of these possibilities, we run assembly simulations in vacuum where the positions and attributes of the ghost particles are randomly-initialized. In this approach, we employ the loss function in Eq. 1, with a single set of target features. We initialize s ("MLForce Scale") at zero and progressively increase it following a sigmoidal function to a maximum value s max . Ideally, as the U GP term grows stronger, the attributes and orientation of the ghost particles will gradually transform to resemble those of the target molecule. This is quantified by the loss per particle (L/n) and by the assembly root mean squared deviation (RMSD), which employs the atom assignments to assess the global structure of the molecule. One difficulty with the assembly RMSD is to take into account atoms that have identical or almost-identical atomic environment vectors, arising from symmetry or pseudo-symmetry in the target molecule. To account for this we enumerate all sets of atoms with near-identical AEVs, using a cutoff of ∑ i ( f if j ) 2 < 3.0, and create an exhaustive list of mappings using each possible permutation of equivalent atoms. We then compute the RMSD using each mapping. As all of the features are non-chiral -that is, they are invariant to reflection -we also compute the RMSD to a reflected copy of the target molecule for each mapping. The lowest RMSD value is then used as the assembly RMSD. We randomly selected 10 molecules (Figure ) from the OpenChem dataset to use as target structures in the assembly simulations. These molecules range from 6 to 50 atoms in size and vary widely in their structures. The set includes heterocycles, branched hydrocarbons, and many examples of both symmetry and pseudo-symmetry, thus providing a challenging test set for assembly. Examples of time series analysis of the assembly simulations for three of these molecules is given in Figure . These simulations were conducted with a maximum MLForce Scale of 5000, which was increased over 100 cycles (of 500 dynamics steps each) and then held constant for an additional 50 cycles. A "two-body" distance restraint was used with a force constant of 0.5 kJ/mol/nm 2 ; note that the effective strength of this term is also modulated by the MLForce Scale.