The quality of the trial/guiding wavefunction does not directly affect
the final DMC estimate of the total energy of a given system (apart
from the fixed node approximation). However, the intrinsic variance
of 
determines the variance of the estimate of the total
energy at each step of the diffusion process. Therefore, as in the
VMC technique, the number of DMC moves required to achieve a specific
variance of the mean, 
, decreases linearly with the
intrinsic variance of . As the computational cost of a DMC
calculation is roughly an order of magnitude greater than that of a
comparable VMC calculation, reducing this intrinsic variance is very
important.
Reducing the intrinsic variance of the trial/guiding wavefunction by
optimisation also improves the numerical stability of a DMC
calculation. As described in section 
, the multiplicity of a
walker at the end of each DMC move is determined by its excess local
energy, 
]. Therefore, any
reduction in the intrinsic variance of 
will reduce the deviation
of the individual multiplicities of the walkers from unity and help to
produce a more stable population.
Finally, any improvement in the quality of should reduce the time
taken for a DMC calculation to reach a converged energy. If is
closer to 
the probability distribution 
(see
section ) starts closer to its converged form. See figure
and section for more details on the
convergence of the DMC algorithm.