  Diffusion Monte Carlo (DMC) is being recognized as a higher-accuracy, albeit
more computationally expensive, alternative to Density Functional Theory (DFT)
for energy predictions of catalytic systems. A major computational bottleneck
in the use of DMC for catalysis is the need to perform finite-size
extrapolations by simulating increasingly large periodic cells (supercells) to
eliminate many-body finite-size effects and obtain energies in the
thermodynamic limit. Here, we show that this computational cost can be
significantly reduced by leveraging the cancellation of many-body finite-size
errors that accompanies the evaluation of energy differences when calculating
quantities like binding energies and mapping potential energy surfaces. We test
the error cancellation and convergence in two well-known adsorbate/slab
systems, H2O/LiH(001) and CO/Pt(111). Based on this, we identify strategies for
obtaining binding energies in the thermodynamic limit that optimize error
cancellation to balance accuracy and computational efficiency. We then predict
the correct order of adsorption site preference on CO/Pt(111), a challenging
problem for DFT. Our accurate, inexpensive DMC calculations recover the top >
bridge > hollow site order, in agreement with experimental observations. We
proceed to map the potential energy surface of CO hopping between Pt(111)
adsorption sites. This reveals the existence of an L-shaped top-bridge-hollow
diffusion trajectory characterized by energy barriers that provide an
additional kinetic justification for experimental observations of CO/Pt(111)
adsorption. Overall, this work demonstrates that it is routinely possible to
achieve order-of-magnitude speedups and memory savings in DMC calculations by
taking advantage of error cancellation in the calculation of energy differences
that are ubiquitous in heterogeneous catalysis and surface chemistry more
broadly.
