LeBeau et al.[ A.I.A.A. paper 2003-1031, 2003] introduced the “virtual subcell” (VSC) method of finding a collision partner for a given particle in a cell. In the VSC method all potential collision partners in the cell are examined to find the nearest neighbor. To limit the CPU time required for large numbers of particles in the cell the search can be restricted to a subset of all particles in the cell; the nearest particle from that restricted search is used. For 3D hexahedral cells, of various aspect ratios, the expected nearest neighbor distance is found to be given (within few percent) by dn = 0.746L/N^0.383. where N is the number of particles in the cell and L is the cube root of the cell volume. Here I test a modification of the VSC method, the “pseudo-subcell” (PSC) method, whereby the search for a collision partner is truncated whenever a “near enough'” particle is found. The “near enough'” distance, or diameter of the pseudo-subcell, is delta = Fdn. For a factor F = 1.1 there is good chance that a “near enough” particle is, in fact, the nearest neighbor. The mean collision separation (MCS) is then found to be less than 1.04dn. Gallis et al. [AIP Conference Proceedings, v1084, pp299-304, 2009.] report that VSC is computationally efficient for N less than 30, so here the VSC search is restricted to 29 remaining particles. The PSC search is restricted to 33 remaining particles, to yield the same MCS as VSC for large N. The limiting (smallest) value of delta for PSC corresponds to that for N = 30. For large N both methods give a MCS value similar to that which would be expected using 35 standard subcells. PSC uses between 12% and 20% less CPU than VSC. PSC can be tailored to give a range of accuracy and CPU saving compared to VSC. There seems to be no need for a standard subcell method; the PSC search routine can be used in all cases merely by limiting delta and the search length
