We demonstrate that four-body real-space Jastrow factors are, with the right type of Jastrow basis function, capable of performing successful wave function stenciling to remove unwanted ionic terms from an overabundant Fermionic reference without unduly modifying the remaining components. In addition to greatly improving size consistency (restoring it exactly in the case of a geminal power), real-space wave function stenciling is, unlike its Hilbert-space predecessors, immediately compatible with diffusion Monte Carlo, allowing it to be used in the pursuit of compact, strongly correlated trial functions with reliable nodal surfaces. We demonstrate the efficacy of this approach in the context of a double bond dissociation by using it to extract a qualitatively correct nodal surface despite being paired with a restricted Slater determinant, that, due to ionic term errors, produces a ground state with a qualitatively incorrect nodal surface when used in the absence of the Jastrow.

We introduce a basis of counting functions that, by cleanly tessellating three-dimensional space, allows real space number counting Jastrow factors to be straightforwardly applied to general molecular situations. By exerting direct control over electron populations in local regions of space and encoding pairwise correlations between these populations, these Jastrow factors allow even very simple reference wave functions to adopt nodal surfaces well suited to many strongly correlated settings. Being trivially compatible with traditional Jastrow factors and diffusion Monte Carlo and having the same cubic per-sample cost scaling as a single determinant trial function, these Jastrow factors thus offer a powerful new route to the simultaneous capture of weak and strong electron correlation effects in a wide variety of molecular and materials settings. In multiple strongly correlated molecular examples, we show that even when paired with the simplest possible single determinant reference, these Jastrow factors allow quantum Monte Carlo to out-perform coupled cluster theory and approach the accuracy of traditional multireference methods.