Bilinear QMC

I'm reading a recent paper by Arias de Saavedra and Kalos titled "Bilinear diffusion quantum Monte Carlo methods" (PRE 67, 026708). They present an algorithm that uses a pair of walkers (the bilinear part) to sample the square of the ground state wavefunction (rather than first power of the wavefunction like DMC).

They claim it's useful for computing unbiased expectation values (see my post from Monday, Feb. 24 - although I'm not sure it would help with derivative operators) and energy differences.

The part I find most intriguing is the way they use importance sampling - they get reasonable results for hydrogen without it. And when they do use importance sampling, it's only to remove singularities due to cusps. I would guess that any successful scheme (ie, able to scale reasonably with system size) needs to use as an accurate a trial wavefunction as possible to guide the sampling.

The more I study the paper, the less I understand it. I guess the first step is to try reproduce their results for the 1-D harmonic oscillator.